Swarm Site Fidelity in the Sex Role-Reversed Dance Fly Empis borealis

In the dance fly species Empis borealis (L.), females (1–40) gather to swarm at landmarks (swarm markers, like trees and bushes), and males carrying an insect prey visit these swarms for mating. We noticed earlier that some swarm sites were used for several years and that they appeared to be frequented by a similar number of swarming females in each year, although the numbers of females varied greatly among swarm sites and certain sites attracted more swarming individuals than others. To explore swarm site fidelity in this mating system, in 1993 we monitored the same swarm sites that we studied in 1989, addressing the questions, Would the same swarm sites still attract the same number of females and males after 4 years? and Why do some swarm sites attract more displaying females than others? The number of females swarming at the different markers in 1993 was approximately the same as 4 years earlier. Some of these swarm sites are known to have been used for 18 years. The swarm sites with the largest number of flies had a high sun exposure during the day and were found at coniferous swarm marker trees and in a mixed forest habitat. A swarm site with few females attending and with a low amount of insolation during the day can be predicted to be abandoned as a swarming site soon. Empis borealis swarm sites thus persist over many years and are attended by a similar number of individuals each year. To our knowledge, such site fidelity has not been demonstrated for any swarming insect species earlier.     

Cryptic variation in butterfly eyespot development: the importance of sample size in gene expression studies

Previous studies have shown that development can be robust to variation in parameters such as the timing or level of gene expression. This leads to the prediction that natural populations should be able to host developmental variation that has little phenotypic effect. Cryptic variation is of particular interest because it can result in selectable phenotypes when "released" by environmental or genetic factors. Currently, however, we have little idea of how variation is distributed between genes or over time in pattern formation processes. Here we survey expression of Notch (N), Spalt (Sal), and Engrailed (En) during butterfly eyespot determination to better understand how pattern formation may vary within a population. We observed substantial heterochronic variance in the progress of spatial expression patterns for all three proteins, suggesting some degree of developmental buffering in eyespot development. Peak variance for different proteins was found at both early and late stages of development, contrasting with previous models suggesting that the distribution of variance should be more temporally focused during pattern formation. We speculate that our observations are representative of a standing reservoir of cryptic variation that may contribute to phenotypic evolution under certain circumstances. Our results also provide a strong cautionary message that gene expression studies with limited sample sizes can be positively misleading in terms of inferring expression pattern time series, as well as for making cross-species phylogenetic comparisons.     

Estimating the In Vivo Killing Efficacy of Cytotoxic T Lymphocytes across Different Peptide-MHC Complex Densities

Cytotoxic T lymphocytes (CTLs) are important agents in the control of intracellular pathogens, which specifically recognize and kill infected cells. Recently developed experimental methods allow the estimation of the CTL''s efficacy in detecting and clearing infected host cells. One method, the in vivo killing assay, utilizes the adoptive transfer of antigen displaying target cells into the bloodstream of mice. Surprisingly, killing efficacies measured by this method are often much higher than estimates obtained by other methods based on, for instance, the dynamics of escape mutations. In this study, we investigated what fraction of this variation can be explained by differences in peptide loads employed in in vivo killing assays. We addressed this question in mice immunized with lymphocytic choriomeningitis virus (LCMV). We conducted in vivo killing assays varying the loads of the immunodominant epitope GP33 on target cells. Using a mathematical model, we determined the efficacy of effector and memory CTL, as well as CTL in chronically infected mice. We found that the killing efficacy is substantially reduced at lower peptide loads. For physiological peptide loads, our analysis predicts more than a factor 10 lower CTL efficacies than at maximum peptide loads. Assuming that the efficacy scales linearly with the frequency of CTL, a clear hierarchy emerges among the groups across all peptide antigen concentrations. The group of mice with chronic LCMV infections shows a consistently higher killing efficacy per CTL than the acutely infected mouse group, which in turn has a consistently larger efficacy than the memory mouse group. We conclude that CTL killing efficacy dependence on surface epitope frequencies can only partially explain the variation in in vivo killing efficacy estimates across experimental methods and viral systems, which vary about four orders of magnitude. In contrast, peptide load differences can explain at most two orders of magnitude.     

Using mathematical models to understand metabolism,genes, and disease

Mathematical models are a useful tool for investigating a large number of questions in metabolism, genetics, and gene–environment interactions. A model based on the underlying biology and biochemistry is a platform for in silico biological experimentation that can reveal the causal chain of events that connect variation in one quantity to variation in another. We discuss how we construct such models, how we have used them to investigate homeostatic mechanisms, gene–environment interactions, and genotype–phenotype mapping, and how they can be used in precision and personalized medicine.     

Enabling Flexible Polymer Tandem Solar Cells by 3D Ptychographic Imaging

The realization of a complete tandem polymer solar cell under ambient conditions using only printing and coating methods on a flexible substrate results in a fully scalable process but also requires accurate control during layer formation to succeed. The serial process where the layers are added one after the other by wet processing leaves plenty of room for error and the process development calls for an analytical technique that enables 3D reconstruction of the layer stack with the possibility to probe thickness, density, and chemistry of the individual layers in the stack. The use of ptychography on a complete 12‐layer solar cell stack is presented and it is shown that this technique provides the necessary insight to enable efficient development of inks and processes for the most critical layers in the tandem stack such as the recombination layer where solvent penetration in fully solution processed 12‐layer stacks is critical in eleven of the steps.     

Single-cell genomics of a rare environmental alphaproteobacterium provides unique insights into Rickettsiaceae evolution

The bacterial family Rickettsiaceae includes a group of well-known etiological agents of many human and vertebrate diseases, including epidemic typhus-causing pathogen Rickettsia prowazekii. Owing to their medical relevance, rickettsiae have attracted a great deal of attention and their host-pathogen interactions have been thoroughly investigated. All known members display obligate intracellular lifestyles, and the best-studied genera, Rickettsia and Orientia, include species that are hosted by terrestrial arthropods. Their obligate intracellular lifestyle and host adaptation is reflected in the small size of their genomes, a general feature shared with all other families of the Rickettsiales. Yet, despite that the Rickettsiaceae and other Rickettsiales families have been extensively studied for decades, many details of the origin and evolution of their obligate host-association remain elusive. Here we report the discovery and single-cell sequencing of ‘Candidatus Arcanobacter lacustris'', a rare environmental alphaproteobacterium that was sampled from Damariscotta Lake that represents a deeply rooting sister lineage of the Rickettsiaceae. Intriguingly, phylogenomic and comparative analysis of the partial ‘Candidatus Arcanobacter lacustris'' genome revealed the presence chemotaxis genes and vertically inherited flagellar genes, a novelty in sequenced Rickettsiaceae, as well as several host-associated features. This finding suggests that the ancestor of the Rickettsiaceae might have had a facultative intracellular lifestyle. Our study underlines the efficacy of single-cell genomics for studying microbial diversity and evolution in general, and for rare microbial cells in particular.     

Predicting the response to simultaneous selection: genetic architecture and physiological constraints

A great deal is known about the evolutionary significance of body size and development time. They are determined by the nonlinear interaction of three physiological traits: two hormonal events and growth rate (GR). In this study we investigate how the genetic architecture of the underlying three physiological traits affects the simultaneous response to selection on the two life-history traits in the hawkmoth Manduca sexta. The genetic architecture suggests that when the two life-history traits are both selected in the same direction (to increase or decrease) the response to selection is primarily determined by the hormonal mechanism. When the life-history traits are selected in opposite directions (one to increase and one to decrease) the response to selection is primarily determined by factors that affect the GR. To determine how the physiological traits affect the response to selection of the life-history traits, we simulated the predicted response to 10 generations of selection. A total of 83% of our predictions were supported by the simulation. The main components of this physiological framework also exist in unicellular organisms, vertebrates, and plants and can thus provide a robust framework for understanding how underlying physiology can determine the simultaneous evolution of life-history traits.