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Sequestration of defenses against predators drives specialized host plant associations in preadapted milkweed bugs (Heteroptera: Lygaeinae)
<p class="CxSpFirst">Host plant specialization across herbivorous insects varies dramatically, but while the molecular mechanisms of host-plant adaptations are increasingly known, we often lack a comprehensive understanding of the selective forces that favor specialization. The milkweed bugs (Heteroptera: Lygaeinae) are engaged in ancestrally specialized associations with plants of the Apocynaceae from which they commonly sequester cardiac glycosides for defense, facilitated by resistant Na<sup>+</sup>/K<sup>+</sup>-ATPases and adaptations for transport, storage and discharge of toxins. Here, we show that three Lygaeinae species independently colonized four novel non-apocynaceous hosts that convergently produce cardiac glycosides. A fourth species shifted to a new source of toxins by tolerating and sequestering alkaloids from meadow saffron (<i>Colchicum autumnale</i>, Colchicaceae). Across three milkweed bug species tested, feeding on seeds containing toxins did not improve growth or speed of development, and even impaired growth and development in two species, but sequestration mediated protection of milkweed bugs against two natural predators: lacewing larvae and passerine birds. We conclude that physiological preadaptations and convergent phytochemistry facilitated novel specialized host associations. Since toxic seeds did not improve but either impaired growth or at most had neutral effects, selection by predators on sequestration of defenses, rather than the exploitation of additional profitable dietary resources, can lead to obligatory specialized host associations in otherwise generalist insects.</p>
A specialist bee and its host plants experience phenological shifts at different rates in response to climate change
<p>Changes in climate can alter the phenology of organisms, potentially decoupling partners within mutualisms. Previous studies have shown that plant and pollinator phenologies are shifting over time, but these shifts have primarily been documented for generalists and within small geographic regions, and the specific climatic cues regulating these shifts are not well-understood. We examined phenological shifts in a specialist pollinator and its host plant species over a 117-year study period using a digitized dataset of over 4,000 unique collection records. We assess how climatic cues regulate these organisms' phenologies using PRISM weather data associated with each record. We tested the hypothesis that rates of phenological change would be greater at northern latitudes. We found that the phenology of the specialist bee pollinator Habropoda laboriosa is changing over time, but at different rates across its range. Specifically, phenology is advancing to a greater degree in more northern populations, with increasing phenological advances of 0.04 days/year with each degree of latitude, and with a delay in phenology in more southern populations. In contrast, only one species in the host plant genus Vaccinium is experiencing phenological change over time. For this plant, rates of change are also variable across latitudes, but in a pattern opposite that of the bee; while phenology is advancing across its range, rates of advance are highest in more southern populations, with decreasing phenological advances of 0.01 days/year with each degree of latitude. The phenologies of both the bee and three of four Vaccinium spp. were regulated primarily by spring temperature, with phenologies overall advancing with increasing temperature, and with the strongest responses shown by the bee in northern populations. Our study provides partial support for the hypothesis that phenologies advance most at northern latitudes, but demonstrates that pollinators and plants do not adhere similarly to this prediction. Additionally, we illustrate the potential for phenological mismatch between a specialist pollinator and its host plants by showing that plants and pollinators are advancing their phenologies at different rates across space and time and with differing responses to changing climatic cues.</p>
FIGURE 5 in Turrana ejuncida, a new species of Acanthocorini (Hemiptera: Heteroptera: Coreidae) from Cape Range, Western Australia, with discussion of its systematic position and host plant associations
FIGURE 5. Map of point localities of Turrana abnormis Distant (triangles) and T. ejuncida sp. nov. (circle). Localities of T. abnormis from Cassis & Gross (2002).
FIGURE 4 in Turrana ejuncida, a new species of Acanthocorini (Hemiptera: Heteroptera: Coreidae) from Cape Range, Western Australia, with discussion of its systematic position and host plant associations
FIGURE 4. Turrana ejuncida sp. nov. Micro-CT images of female terminalia (WAME106180). A) dorsal, B) ventral, and C) lateral views of tip of abdomen. Scale bar = 100 µm.
FIGURE 3 in Turrana ejuncida, a new species of Acanthocorini (Hemiptera: Heteroptera: Coreidae) from Cape Range, Western Australia, with discussion of its systematic position and host plant associations
FIGURE 3. Turrana ejuncida sp. nov. Micro-CT images of male genitalia (WAME106179). A) pygophore and semi-inflated aedeagus, lateral view; sclerotized portions of conjunctival processes coloured green. B) anterior of aedeagus. C) right paramere. Scale bars = 100 µm.
FIGURE 2 in Turrana ejuncida, a new species of Acanthocorini (Hemiptera: Heteroptera: Coreidae) from Cape Range, Western Australia, with discussion of its systematic position and host plant associations
FIGURE 2. Scanning electron micrographs of Turrana ejuncida sp. nov. female (WAME106180). A) head, lateral; B) head, dorsal; C) head and thorax, ventral; D) pronotum, dorsal; E) hemelytra, detail; F) metathoracic scent gland. Anterior to left in all images.
FIGURE 1 in Turrana ejuncida, a new species of Acanthocorini (Hemiptera: Heteroptera: Coreidae) from Cape Range, Western Australia, with discussion of its systematic position and host plant associations
FIGURE 1. Turrana ejuncida sp. nov. dorsal and lateral habitus images. A, B) holotype male (WAME106179); C, D) paratype female (WAME106180).
FIGURE 6 in Turrana ejuncida, a new species of Acanthocorini (Hemiptera: Heteroptera: Coreidae) from Cape Range, Western Australia, with discussion of its systematic position and host plant associations
FIGURE 6. Collecting sites of Turrana ejuncida sp. nov. in Cape Range National Park. A) flowering Ipomoea yardiensis (detail in inset) on remote rocky ridge adjacent to canyon. B) Triodia epactia (inset shows dry, brown underside of plant) at side of Charles Knife Canyon Road, on ridge.
Host genetics, phenotype and geography structure the microbiome of a foundational seaweed
<p>Interactions between hosts and their microbiota are critical to the functioning and resilience of eukaryotic macro-organisms. Critically, for hosts that play foundational roles in communities, understanding what drives these interactions is essential for informing restoration and conservation of entire ecosystems. Here, we investigated the relative influence of host traits and the surrounding environment on microbial communities associated with the foundational seaweed Phyllospora comosa. We collected data on 16 morphological and functional phenotypic traits, host genetics (using 354 Single Nucleotide Polymorphisms) and surface-associated microbial communities (using 16S rRNA gene amplicon sequencing) from 160 individuals sampled from eight sites spanning Phyllospora's entire latitudinal distribution (1300 km). Combined, these factors explained 54% of the overall variation in Phyllospora's associated microbial community structure, much of which was related to the local environment (~32%). We found that putative "core" microbial taxa (i.e. present on all Phyllospora individuals sampled) exhibited slightly higher association with host traits when compared to "variable" taxa (not present on all individuals). We identified several key genetic loci and phenotypic traits in Phyllospora that were strongly related to multiple microbial amplicon sequence variants, including taxa with known associations to seaweed defense, disease and tissue degradation. This information on how host-associated microbial communities vary with host traits and the environment enhances our current understanding of holobionts and how they are structured. Such understanding can be used to inform management strategies of these important and vulnerable habitats.</p>
◂Fig. 5 Ramisyllis kingghidorahi n. sp. and host sponge Petrosia sp. A Anterior region in dorsal view, prostomium faces down. B Fragment of one specimen. C-F–f Host sponges in their natural habitat. Scale bars: 2 mm A, B, 1 cm C, D and 5 mm E, F in Ramisyllis kingghidorahi n. sp., a new branching annelid from Japan
◂Fig. 5 Ramisyllis kingghidorahi n. sp. and host sponge Petrosia sp. A Anterior region in dorsal view, prostomium faces down. B Fragment of one specimen. C-F–f Host sponges in their natural habitat. Scale bars: 2 mm A, B, 1 cm C, D and 5 mm E, F
FIGURE. Phylogenetic tree of specimens on Poaceae and related host plants constructed by MP method based on ITS+28S regions of rDNA. Bootstrap values of MP and ML are followed by the Bayesian posterior probabilities (Bpp) on the nodes in the topology. Asterisk (*) represents bootstrap values or Bpp less than 50% in the topology. Sample data are shown with voucher specimen number or GenBank accession number, and host plant. Sequence data determined in this study are shown in color. Teliospore shapes are shown in each clade detected, and new species are shown by asterisk (*) on clades. 0, I: Spermogonial and aecial host genus. Asterisk (*) on host plants: Spermogonial and aecial host plants. in Phylogenetic approach for identification and life cycles of Puccinia (Pucciniaceae) species on Poaceae from northeastern China
FIGURE. Phylogenetic tree of specimens on Poaceae and related host plants constructed by MP method based on ITS+28S regions of rDNA. Bootstrap values of MP and ML are followed by the Bayesian posterior probabilities (Bpp) on the nodes in the topology. Asterisk (*) represents bootstrap values or Bpp less than 50% in the topology. Sample data are shown with voucher specimen number or GenBank accession number, and host plant. Sequence data determined in this study are shown in color. Teliospore shapes are shown in each clade detected, and new species are shown by asterisk (*) on clades. 0, I: Spermogonial and aecial host genus. Asterisk (*) on host plants: Spermogonial and aecial host plants.
FIGURE. Phylogenetic relationships among species on Poaceae shown with synoptic phylogenetic tree constructed by MP method based on ITS+28S regions of rDNA. Same color branches show phylogenetic groups. 0, I: Spermogonial and aecial host genus. in Phylogenetic approach for identification and life cycles of Puccinia (Pucciniaceae) species on Poaceae from northeastern China
FIGURE. Phylogenetic relationships among species on Poaceae shown with synoptic phylogenetic tree constructed by MP method based on ITS+28S regions of rDNA. Same color branches show phylogenetic groups. 0, I: Spermogonial and aecial host genus.
Data from: The effects of phylogeny, habitat, and host characteristics on the thermal sensitivity of helminth development
<p>Helminth parasites are part of almost every ecosystem, with more than 300 000 species worldwide. Helminth infection dynamics are expected to be altered by climate change, but predicting future changes is difficult due to lacking thermal sensitivity data for greater than 99.9% of helminth species. Here, we compiled the largest dataset to date on helminth temperature sensitivities and used the Metabolic Theory of Ecology to estimate activation energies (AEs) for parasite developmental rates. The median AE for 129 thermal performance curves was 0.67, similar to non-parasitic animals. Although exceptions existed, related species tended to have similar thermal sensitivities, suggesting some helminth taxa are inherently more affected by rising temperatures than others. Developmental rates were more temperature-sensitive for species from colder habitats than those from warmer habitats, and more temperature sensitive for species in terrestrial than aquatic habitats. AEs did not depend on whether helminth life stages were free-living or within hosts, whether the species infected plants or animals, or whether the species had an endotherm host in its life cycle. The phylogenetic conservatism of AE may facilitate predicting how temperature change affects the development of helminth species for which empirical data are lacking or difficult to obtain.Helminth parasites are part of almost every ecosystem, with more than 300 000 species worldwide. Helminth infection dynamics are expected to be altered by climate change, but predicting future changes is difficult due to lacking thermal sensitivity data for greater than 99.9% of helminth species. Here, we compiled the largest dataset to date on helminth temperature sensitivities and used the Metabolic Theory of Ecology to estimate activation energies (AEs) for parasite developmental rates. The median AE for 129 thermal performance curves was 0.67, similar to non-parasitic animals. Although exceptions existed, related species tended to have similar thermal sensitivities, suggesting some helminth taxa are inherently more affected by rising temperatures than others. Developmental rates were more temperature-sensitive for species from colder habitats than those from warmer habitats, and more temperature sensitive for species in terrestrial than aquatic habitats. AEs did not depend on whether helminth life stages were free-living or within hosts, whether the species infected plants or animals, or whether the species had an endotherm host in its life cycle. The phylogenetic conservatism of AE may facilitate predicting how temperature change affects the development of helminth species for which empirical data are lacking or difficult to obtain.</p>
Impact of New Variants on SARS-CoV-2 Infectivity and Neutralization: A Molecular Assessment of the Alterations in the Spike-Host Protein Interactions
<p>MD simulation trajectories and structural models from the work which first appeared on bioRxiv (https://doi.org/10.1101/2021.01.10.426143), later ssrn (<a href="https://dx.doi.org/10.2139/ssrn.3907841">http://dx.doi.org/10.2139/ssrn.3907841</a>), and finally accepted for publication by Iscience.</p> <p>File Name: <a href="https://zenodo.org/api/files/d5ac679d-c267-4e55-8f63-0abdaa41d067/Run1_WT_RBD_ACE2.zip">Run1_WT_RBD_ACE2.zip</a></p> <p>Description: A compressed (zipped) folder contains three independent MD trajectories of WT RBD-ACE2 complex.</p> <p>File Name: <a href="https://zenodo.org/api/files/d5ac679d-c267-4e55-8f63-0abdaa41d067/Run2_N501Y_RBD_ACE2.zip">Run2_N501Y_RBD_ACE2.zip</a></p> <p>Description: A compressed folder contains three independent MD trajectories of Alpha RBD-ACE2 complex.</p> <p>File Name: <a href="https://zenodo.org/api/files/d5ac679d-c267-4e55-8f63-0abdaa41d067/Run3_Beta_RBD_ACE2.zip">Run3_Beta_RBD_ACE2.zip</a></p> <p>Description: A compressed folder contains three independent MD trajectories of Beta RBD-ACE2 complex.</p> <p>File Name: <a href="https://zenodo.org/api/files/d5ac679d-c267-4e55-8f63-0abdaa41d067/Run4_Delta_RBD_ACE2.zip">Run4_Delta_RBD_ACE2.zip</a></p> <p>Description: A compressed folder contains three independent MD trajectories of Delta RBD-ACE2 complex</p> <p>File Name: <a href="https://zenodo.org/api/files/d5ac679d-c267-4e55-8f63-0abdaa41d067/Run5_UK2_E484K_N501Y_ACE2.zip">Run5_UK2_E484K_N501Y_ACE2.zip</a></p> <p>Description: A compressed folder contains three independent MD trajectories of UK2 RBD-ACE2 complex</p> <p>File Name: <a href="https://zenodo.org/api/files/d5ac679d-c267-4e55-8f63-0abdaa41d067/Structural_model_PDBs.zip">Structural_model_PDBs.zip</a></p> <p>Description: A compressed folder contains eight pdb files of those structural models plotted in Figs 1, 3, 5, 6, 7 and S1.</p>
Fig. 2. A in Limosilactobacillus balticus sp. nov., Limosilactobacillus agrestis sp. nov., Limosilactobacillus albertensis sp. nov., Limosilactobacillus rudii sp. nov. and Limosilactobacillus fastidiosus sp. nov., five novel Limosilactobacillus species isolated from the vertebrate gastrointestinal tract, and proposal of six subspecies of Limosilactobacillus reuteri adapted to the gastrointestinal tract of specific vertebrate hosts
Fig. 2. A maximum-likelihood phylogenetic tree reconstructed using core genes (n=100) identified from whole-genome sequences, showing the evolutionary relationships among five novel Limosilactobacillus species, six L. reuteri subspecies and other recognized species in the genus Limosilactobacillus. GenBank or JGI accession numbers of these genomes are provided in parentheses. The tree was inferred based on the GTR+G model with 1000 bootstrap replicates and only bootstrap values above 60% are shown. Strains of five novel Limosilactobacillus species are labelled by different colours; labels of six L. reuteri subspecies are colour representing vertebrate host origin: green for rodents, red for pigs, blue for humans and orange for poultry. The tree was drawn with iTOL [54].
Fig. 1. A maximum-likelihood phylogenetic tree reconstructed using 16S in Limosilactobacillus balticus sp. nov., Limosilactobacillus agrestis sp. nov., Limosilactobacillus albertensis sp. nov., Limosilactobacillus rudii sp. nov. and Limosilactobacillus fastidiosus sp. nov., five novel Limosilactobacillus species isolated from the vertebrate gastrointestinal tract, and proposal of six subspecies of Limosilactobacillus reuteri adapted to the gastrointestinal tract of specific vertebrate hosts
Fig. 1. A maximum-likelihood phylogenetic tree reconstructed using 16S rRNA gene sequences. GenBank or JGI accession numbers of these genomes are provided in parentheses. The tree was inferred based on the GTR+G model with 1000 bootstrap replicates and only bootstrap values above 60% are shown. Strains of five novel Limosilactobacillus species are labelled by different colours; labels of six L. reuteri subspecies are colour representing vertebrate host origin: green for rodents, red for pigs, blue for humans and orange for poultry. The tree was drawn with iTOL [54].
Fig. 3. A in Limosilactobacillus balticus sp. nov., Limosilactobacillus agrestis sp. nov., Limosilactobacillus albertensis sp. nov., Limosilactobacillus rudii sp. nov. and Limosilactobacillus fastidiosus sp. nov., five novel Limosilactobacillus species isolated from the vertebrate gastrointestinal tract, and proposal of six subspecies of Limosilactobacillus reuteri adapted to the gastrointestinal tract of specific vertebrate hosts
Fig. 3. A maximum-likelihood phylogenetic tree reconstructed using core genes (n=100) identified from whole-genome sequences, showing the evolutionary relationships among six L. reuteri subspecies. The tree was reconstructed using 33 L. reuteri genomes available in public databases (n=6 for L. reuteri subsp. kinnaridis, n=2 for L. reuteri subsp. porcinus, n=5 for L. reuteri subsp. murium, n=10 for L. reuteri subsp. reuteri, n=5 for L. reuteri subsp. suis and n=5 for L. reuteri subsp. rodentium) and L. balticus BG-AF3-AT was used as an outgroup. Further information on the involved genome sequences is listed in Table S1. The tree was inferred based on the GTR+G model with 1000 bootstrap replicates and only bootstrap values above 60% are shown. The tree was drawn with iTOL [54].
Fig. 4 in Limosilactobacillus balticus sp. nov., Limosilactobacillus agrestis sp. nov., Limosilactobacillus albertensis sp. nov., Limosilactobacillus rudii sp. nov. and Limosilactobacillus fastidiosus sp. nov., five novel Limosilactobacillus species isolated from the vertebrate gastrointestinal tract, and proposal of six subspecies of Limosilactobacillus reuteri adapted to the gastrointestinal tract of specific vertebrate hosts
Fig. 4. Pairwise average nucleotide identity values (ANI; %) of genome sequences belonging to the same or different L. reuteri subspecies. ANI values within the same subspecies and between different subspecies were calculated for 33 L. reuteri genomes available in public databases (n=6 for L. reuteri subsp. kinnaridis, n=2 for L. reuteri subsp. porcinus, n=5 for L. reuteri subsp. murium, n=10 for L. reuteri subsp. reuteri, n=5 for L. reuteri subsp. suis and n=5 for L. reuteri subsp. rodentium). Further information on the involved genome sequences is listed in Table S1.
DNA barcoding reveals generalization and host overlap in hummingbird flower mites: implications for the Mating Rendezvous Hypothesis
Hummingbird flower mites are assumed to monopolize single host plant species due to sexual selection for unique mating rendezvous sites. We tested the main assumption of the Mating rendezvous hypothesis -extreme host specialization- by reconstructing interactions among tropical hummingbird flower mites and their host plants using DNA barcoding and taxonomic identifications. We collected 10,654 mites from 489 flowers. We extracted DNA from 1928 mite specimens and amplified the cytochrome c oxidase I (CO1) DNA barcode. We analyzed the network structure to assess the degree of generalization or specialization of mites to their host plants. We recorded 18 species of hummingbird flower mites from three genera (Proctolaelaps, Rhinoseius and Tropicoseius) interacting with 14 species of plants. We found that generalist mites are common, and congeneric mite species often share host plants. Our results challenge the assumption of strict specialization that supports this system as an example of mating rendezvous evolution.
Larval parasitism in a specialist herbivore is explained by phenological synchrony and host plant availability
<p class="MsoNormal"><span>Parasitism is a key factor in the population dynamics of many herbivorous insects, although its impact on host populations varies widely, for instance, along latitudinal and altitudinal gradients. Understanding the sources of geographical variation in host-parasitoid interactions is crucial for reliably predicting the future success of the interacting species under a context of global change.</span></p> <p class="MsoNormal"><span>Here, we examine larval parasitism in the butterfly <em>Aglais urticae</em> in south-west Europe, where it is a mountain specialist. Larval nests were sampled over two years along altitudinal gradients in three Iberian mountain ranges, including the Sierra Nevada, home to its southernmost European population. Additional data on nettle condition and adult butterflies were obtained in the study areas. </span></p> <p class="MsoNormal"><span>These data sources were used to investigate whether or not differences in parasitism rates are related to the geographical position and phenology of the host, and to the availability of the host plants.</span></p> <p class="MsoNormal"><span>Phenological differences in the host populations between regions were related to the severity of summer drought and the corresponding differences in host plant availability. At the </span><span>trailing-edge </span><span>of its distribution, the butterfly's breeding season was restricted to the end of winter and spring, while in its northern Iberian range the season was prolonged until mid-summer. Although parasitism was an important source of mortality in all regions, parasitism rates and parasitoid richness were highest in the north and lowest in the south. Moreover, within a region, there was a notable increase in parasitism rates over time, which probably led to selection against an additional late-summer host generation in northern regions. Conversely, the shorter breeding season in Sierra Nevada resulted in a loss of synchrony between the host and one important late-season parasitoid, <em>Sturmia bella</em>, which may partly explain the high density of this butterfly species at the </span><span>trailing-edge </span><span>of its range.</span></p> <p class="MsoNormal"><span>Our results support the key role of host phenology in accounting for differences in parasitism rates between populations. They also provide insights into how climate through host plant availability affects host phenology and, ultimately, the impact of parasitism on host populations.</span></p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.