The long-distance flight behavior of Drosophila supports an agent-based model for wind-assisted dispersal in insects.

Despite the ecological importance of long-distance dispersal in insects, its mechanistic basis is poorly understood in genetic model species, in which advanced molecular tools are readily available. One critical question is how insects interact with the wind to detect attractive odor plumes and increase their travel distance as they disperse. To gain insight into dispersal, we conducted release-and-recapture experiments in the Mojave Desert using the fruit fly, Drosophila melanogaster We deployed chemically baited traps in a 1 km radius ring around the release site, equipped with cameras that captured the arrival times of flies as they landed. In each experiment, we released between 30,000 and 200,000 flies. By repeating the experiments under a variety of conditions, we were able to quantify the influence of wind on flies' dispersal behavior. Our results confirm that even tiny fruit flies could disperse ∼12 km in a single flight in still air and might travel many times that distance in a moderate wind. The dispersal behavior of the flies is well explained by an agent-based model in which animals maintain a fixed body orientation relative to celestial cues, actively regulate groundspeed along their body axis, and allow the wind to advect them sideways. The model accounts for the observation that flies actively fan out in all directions in still air but are increasingly advected downwind as winds intensify. Our results suggest that dispersing insects may strike a balance between the need to cover large distances while still maintaining the chance of intercepting odor plumes from upwind sources.

Correlations Between LC-MS/MS-Detected Glycomics and NMR-Detected Metabolomics in Caenorhabditis elegans Development.

This study examined the relationship between glycans, metabolites, and development in C. elegans. Samples of N2 animals were synchronized and grown to five different time points ranging from L1 to a mixed population of adults, gravid adults, and offspring. Each time point was replicated seven times. The samples were each assayed by a large particle flow cytometer (Biosorter) for size distribution data, LC-MS/MS for targeted N- and O-linked glycans, and NMR for metabolites. The same samples were utilized for all measurements, which allowed for statistical correlations between the data. A new protocol was developed to correlate Biosorter developmental data with LC-MS/MS data to obtain stage-specific information of glycans. From the five time points, four distinct sizes of worms were observed from the Biosorter distributions, ranging from the smallest corresponding to L1 to adult animals. A network model was constructed using the four binned sizes of worms as starting nodes and adding glycans and metabolites that had correlations with r ≥ 0.5 to those nodes. The emerging structure of the network showed distinct patterns of N- and O-linked glycans that were consistent with previous studies. Furthermore, some metabolites that were correlated to these glycans and worm sizes showed interesting interactions. Of note, UDP-GlcNAc had strong positive correlations with many O-glycans that were expressed in the largest animals. Similarly, phosphorylcholine correlated with many N-glycans that were expressed in L1 animals.

Dereplication of plant phenolics using a mass-spectrometry database independent method.

INTRODUCTION: Dereplication, an approach to sidestep the efforts involved in the isolation of known compounds, is generally accepted as being the first stage of novel discoveries in natural product research. It is based on metabolite profiling analysis of complex natural extracts. OBJECTIVE: To present the application of LipidXplorer for automatic targeted dereplication of phenolics in plant crude extracts based on direct infusion high-resolution tandem mass spectrometry data. MATERIAL AND METHODS: LipidXplorer uses a user-defined molecular fragmentation query language (MFQL) to search for specific characteristic fragmentation patterns in large data sets and highlight the corresponding metabolites. To this end, MFQL files were written to dereplicate common phenolics occurring in plant extracts. Complementary MFQL files were used for validation purposes. RESULTS: New MFQL files with molecular formula restrictions for common classes of phenolic natural products were generated for the metabolite profiling of different representative crude plant extracts. This method was evaluated against an open-source software for mass-spectrometry data processing (MZMine®) and against manual annotation based on published data. CONCLUSION: The targeted LipidXplorer method implemented using common phenolic fragmentation patterns, was found to be able to annotate more phenolics than MZMine® that is based on automated queries on the available databases. Additionally, screening for ascarosides, natural products with unrelated structures to plant phenolics collected from the nematode Caenorhabditis elegans, demonstrated the specificity of this method by cross-testing both groups of chemicals in both plants and nematodes.

Metabolomics and Natural-Products Strategies to Study Chemical Ecology in Nematodes.

This review provides an overview of two complementary approaches to identify biologically active compounds for studies in chemical ecology. The first is activity-guided fractionation and the second is metabolomics, particularly focusing on a new liquid chromatography-mass spectrometry-based method called isotopic ratio outlier analysis. To illustrate examples using these approaches, we review recent experiments using Caenorhabditis elegans and related free-living nematodes.

Evolution of Manduca sexta hornworms and relatives: biogeographical analysis reveals an ancestral diversification in Central America.

The hawkmoth genus Manduca is a diverse group of very large, conspicuous moths that has served as an important model across many biological disciplines. Two species in particular, the tobacco hornworm (Manduca sexta) and the tomato hornworm (Manduca quinquemaculatus) have been researched extensively. Studies across biological fields have referred to these two species as being closely related or even sister species, but the extent to which these two model organisms are related remains largely unknown. We conducted a comprehensive multi-gene phylogenetic analysis of Manduca, based on both an ML and Bayesian framework, which resulted in a monophyletic Manduca but only when two other genera, Dolba and Euryglottis are included. We tentatively conclude that the sister group to Manduca sexta comprises the Caribbean M. afflicta and M. johanni, and the sister lineage to this clade includes M. quinquemaculatus and the Hawaiian M. blackburni. Thus, M. sexta and M. quinquemaculatus are closely related, but are not sister species. Biogeographical analyses reveal an ancestral center of diversification in Central America, and Manduca appears to have subsequently colonized North and South America. Our phylogeny provides an important foundation for comparative studies of two model organisms and their relatives.