Biology subjects

Gillespie, R.

Publications and source records attributed to Gillespie, R..

11 recordsLinked to original sources

bioRxiv2026

Spiders as natural DNA samplers recover arthropod community diversity and biotic interactions across space and time

Global arthropod decline demands effective biodiversity monitoring strategies. However, most current monitoring approaches do not provide an exhaustive picture of arthropod community structure. In particular, biotic interactions and temporal patterns of biodiversity change are still poorly understood. Here we explore the possibility of addressing these two shortfalls using spiders, one of the most important predators of terrestrial arthropods, as natural samplers for arthropod community DNA. We conducted several experiments comparing the recovered community composition between spider gut contents and traditional monitoring methods. Additionally, we used archived spiders from long-term collections to assess the preservation of prey DNA over time. Spiders proved to be highly efficient natural DNA samplers, with gut content metabarcoding revealing similar community composition and alpha- and beta-diversity like traditional methods. Unique arthropod taxa were detected by spider gut contents and traditional methods respectively, indicating that these two approaches can serve as valuable complements to each other. Well-preserved archived spiders effectively reconstructed historical diets up to 20 years back in time, showing that historical spider collections can act as time capsules of the wider diversity that occurred in the spider's habitat. Spiders as natural samplers overcome critical shortfalls in biodiversity monitoring and contribute to our future understanding of community assembly across space and time.

ecology↗

bioRxiv2026

Increased stress in early life epigenetically rewires pathways related to aging and longevity

Environmental conditions experienced early in life have profound consequences for vertebrate health, yet the molecular pathways linking developmental stress to aging and reduced lifespan remain poorly understood. Through a novel highly accurate epigenetic clock, developed from RRBS-based blood DNA methylation profiles, we show that experimental lifespan-reducing early-life stress rapidly accelerates epigenetic age in zebra finch chicks (Taeniopygia guttata). Corticosterone-treated 29-day-old chicks share differentially methylated loci with non-treated aged birds and cluster with 6-month-old birds. The transcriptional repressor ZBTB16 emerges as an epigenetically top age-correlated gene and is strongest affected by corticosterone. Elevated developmental corticosterone causes rapid epigenetic remodelling of metabolic pathways well-established in aging and longevity. Our results demonstrate epigenetic rewiring of the aging trajectory through conserved stress-survival mechanisms immediately following elevated early-life stress exposure.

developmental biology↗

bioRxiv2026

Extraction workflow determines marker-specific recovery andreproducibility in leaf-litter eDNA metabarcoding

Forest-floor leaf litter is a dynamic and structurally complex ecological transition zone and thus a promising substrate for terrestrial eDNA metabarcoding. Yet, extraction workflows for this heterogeneous matrix remain poorly standardized, especially in tropical systems, making it largely impossible to compare ecological functions across space, time, and taxa. To guide workflow selection across a series of selection criteria, including biological target, research question and practical considerations, we compared DNA extraction workflows for leaf-litter eDNA collected from 42 biological samples across seven different forest sites on Oahu, Hawaii. We evaluated four DNA extraction workflows: (1) Two low-volume approaches, with DNA extracted directly from 200 mg of homogenized litter using (i) CTAB or (ii) DNeasy PowerSoil(R); and (2) two high-volume approaches using PBS wash-based from 10 g of litter followed by (i) Centrifugation or (ii) Filtration. Taxonomic recovery from each workflow was evaluated with two COI primer sets targeting arthropods (ANML and shorter NoPlant), and one ITS marker targeting fungi. Results show that eDNA workflows tested here recovered site-level differences among forest-floor communities, but biodiversity recovery depended strongly on extraction workflow and marker. For low volumes, PowerSoil recovered the highest fungal richness (with ITS marker), and produced the most reproducible PCR-replicate profiles across markers, and required the least hands-on time, while CTAB was less expensive but required handling hazardous chemicals. For high volumes workflow, Centrifugation recovered higher arthropod diversity with ANML primer. Differences in community composition were nonetheless recovered by each method. At the same time, sampling sites explained more ASV-level compositional variation than extraction workflow across markers, showing that all workflows retained site-level ecological signals. Together, these results support a workflow framework in which extraction choice depends on target organism group, DNA state, reproducibility needs, and practical constraints.

ecology↗

bioRxiv2026

Emerging Beetle-Pathogen Symbioses and Their Consequences for Forest Health: Lessons from Rapid 'Ohi'a Death in Hawai'i

Invasive ambrosia beetles and fungal pathogens threaten forest ecosystems worldwide, exemplified in Hawaii by the widespread loss of keystone species [o]hia (Metrosideros polymorpha), due to Rapid [O]hia Death (ROD). A unique occurrence of five ambrosia beetle species (one native, four introduced) that vary in their symbiotic relationships with two introduced fungal pathogens provide an opportunity to test hypotheses of how opportunistic symbioses facilitate disease dynamics involving dominant forest trees. ROD is caused by two novel Ceratocystis fungal pathogens whose spores can spread via association with ambrosia beetles as they bore into [o]hia trees. We examined beetle-pathogen interactions of all five ambrosia beetle species in three ROD-affected regions on Hawaii Island, and used quantitative PCR (qPCR) to provide the first molecular confirmation of the two ROD pathogens associated with the exterior, mycangia, and gut of each beetle species. Results from generalized linear models and correlation networks show that pathogen acquisition and transport, including the potential for consumption and the presence of the pathogens, are determined by beetle invasion status and mycangia morphology. A niche construction framework suggests that both varying symbioses and opportunism facilitate disease spread, with the three invasive Xyleborus species emerging as key disease vectors. Identifying the beetle species that are more likely to contribute to disease spread, and understanding their biology as vectors, can inform targeted conservation strategies for [o]hia and for insect-pathogen threats in forests worldwide, and illustrates the potential ecosystem-level impacts of novel and opportunistic symbioses between globally distributed invasive vectors and pathogens.

ecology↗

bioRxiv2026

Topography structures of arthropod communities revealed by leaf-derived environmental DNA on Oahu, Hawaii

Arthropod communities on oceanic islands are shaped by spatial isolation, environmental gradients, and biological invasions, yet their structure remains difficult to resolve due to incomplete taxonomic coverage. In particular, it remains unclear (i) how non-native arthropods can influence community composition and (ii) how they interact with native and non-native plants. To answer the first question, we used leaf-derived environmental DNA (eDNA) to characterize arthropod communities across elevational gradients on five ridges on Oahu, using the native tree Metrosideros polymorpha as a standardized plant. To understand the second question, we compared leaf-derived eDNA from Metrosideros polymorpha (Native), Acacia koa (native), and Psidium cattleianum (invasive), co-occurring in two ridges on Oahu. Additionally, to overcome limitations of reference databases, we applied NIClassify to infer native versus introduced status without requiring species-level identification. Across 96 leaf samples (with 851 Arthropod ASVs), we found arthropod richness increased with elevation, while the proportion of introduced taxa declined significantly. Community composition was primarily structured by ridge, with strong distance-decay relationships indicating high spatial turnover in both native and non-native assemblages. In contrast, plant species effects were context dependent and did not show a consistent native versus invasive signal. Threshold analyses identified a community transition (native vs introduced) near 500 m elevation. These results show that plant-derived eDNA can resolve spatial and environmental structuring of arthropod communities while capturing invasion dynamics under incomplete taxonomic knowledge. Classifier-based inference enables community-level ecological interpretation beyond reference-limited taxa, providing a scalable framework for biodiversity monitoring in data-poor systems.

ecology↗

bioRxiv2026

Comparison of environmental DNA and bulk DNA metabarcoding for assessing terrestrial arthropod diversity across three habitat types on Guam

DNA based methods offer a rapid and cost-effective way for detecting species occurrence and monitoring biodiversity; among them bulk DNA metabarcoding is well-established, and recently developed environmental DNA (eDNA)-based methods offer a non-destructive alternative. With a goal to develop suitable methods for assessing insect biodiversity in ecosystems for which DNA reference libraries are not well developed and incomplete, such as remote islands, we compared established bulk DNA metabarcoding methods with eDNA across three replicated terrestrial ecosystem types (limestone forest, degraded forest, and grassland) in Guam. Using two mitochondrial COI primer pairs, we performed bulk DNA metabarcoding of standard entomological collection methods (malaise traps, pan traps, vegetation beating), and compared the assessment of biodiversity with that from different eDNA sources (flowers, spider webs, leaves, tree trunks). In our samples, eDNA and bulk DNA metabarcoding both detected a large proportion of overall taxa (OTUs, 86.6% and 60.3%, respectively). Although DNA metabarcoding detected significantly more taxa, eDNA proved to be a reasonable non-destructive alternative. As expected, because of limitations in existing reference databases for remote habitats, species-level identification was achieved for only a few OTUs. Overall, the sampling approach was the dominant driver of arthropod diversity, explaining [~]17% of the observed variation, while habitat type accounted for [~]4%. Thus, each sampling approach captured some unique diversity signals and contributed to the complementary effect of maximizing detection. For rapid insect biodiversity surveys of terrestrial arthropods, we recommend an integrated metabarcoding approach, and in sensitive habitats where insect capture is undesirable, eDNA offers a powerful alternative to monitor diversity and community change.

ecology↗

bioRxiv2025

From sequence to scaffold: computational design of protein nanoparticle vaccines from AlphaFold2-predicted building blocks

Self-assembling protein nanoparticles are being increasingly utilized in the design of next-generation vaccines due to their ability to induce antibody responses of superior magnitude, breadth, and durability. Computational protein design offers a route to novel nanoparticle scaffolds with structural and biochemical features tailored to specific vaccine applications. Although strategies for designing new self-assembling proteins have been established, the recent development of powerful machine learning-based tools for protein structure prediction and design provides an opportunity to overcome several of their limitations. Here, we leveraged these tools to develop a generalizable method for designing novel self-assembling proteins starting from AlphaFold2 predictions of oligomeric protein building blocks. We used the method to generate six new 60-subunit protein nanoparticles with icosahedral symmetry, and single-particle cryo-electron microscopy reconstructions of three of them revealed that they were designed with atomic-level accuracy. To transform one of these nanoparticles into a functional immunogen, we reoriented its termini through circular permutation, added a genetically encoded oligomannose-type glycan, and displayed a stabilized trimeric variant of the influenza hemagglutinin receptor binding domain through a rigid de novo linker. The resultant immunogen elicited potent receptor-blocking and neutralizing antibody responses in mice. Our results demonstrate the practical utility of machine learning-based protein modeling tools in the design of nanoparticle vaccines. More broadly, by eliminating the requirement for experimentally determined structures of protein building blocks, our method dramatically expands the number of starting points available for designing new self-assembling proteins. Significance StatementSelf-assembling protein nanoparticle vaccines have steadily gained traction in both academic and industry vaccine development over the last decade. Recent work has shown that computationally designing new self-assembling proteins allows the structural and functional features of nanoparticle vaccines to be precisely tailored, and that this can significantly affect the vaccine-elicited immune response. To date, designing such nanoparticle vaccines has required the use of known crystal structures as starting points. Here we show how new machine learning tools can be leveraged to design new self-assembling protein nanoparticle immunogens in the absence of experimentally determined structures of the building blocks that elicit strong immune responses in mice.

biochemistry↗

bioRxiv2023

Antigen spacing on protein nanoparticles influences antibody responses to vaccination

Immunogen design approaches aim to control the specificity and quality of antibody responses to enable the creation of next-generation vaccines with improved potency and breadth. However, our understanding of the relationship between immunogen structure and immunogenicity is limited. Here we use computational protein design to generate a self-assembling nanoparticle vaccine platform based on the head domain of influenza hemagglutinin (HA) that enables precise control of antigen conformation, flexibility, and spacing on the nanoparticle exterior. Domain-based HA head antigens were presented either as monomers or in a native-like closed trimeric conformation that prevents exposure of trimer interface epitopes. These antigens were connected to the underlying nanoparticle by a rigid linker that was modularly extended to precisely control antigen spacing. We found that nanoparticle immunogens with decreased spacing between closed trimeric head antigens elicited antibodies with improved hemagglutination inhibition (HAI) and neutralization potency as well as binding breadth across diverse HAs within a subtype. Our "trihead" nanoparticle immunogen platform thus enables new insights into anti-HA immunity, establishes antigen spacing as an important parameter in structure-based vaccine design, and embodies several design features that could be used to generate next-generation vaccines against influenza and other viruses. HIGHLIGHTSO_LIComputational design of a closed trimeric HA head ("trihead") antigen platform. C_LIO_LIDesign of a rigid, extendable linker between displayed antigen and underlying protein nanoparticle enables precise variation of antigen spacing. C_LIO_LIDecreased antigen spacing of triheads elicits antibodies with the highest HAI, neutralizing activity, and cross-reactivity. C_LIO_LIChanges to antigen spacing alter epitope specificities of vaccine-elicited antibodies. C_LI

immunology↗

bioRxiv2020

A holobiont view of island biogeography: unraveling patterns driving the nascent diversification of a Hawaiian spider and its microbial associates

The diversification of a host lineage can be influenced by both the external environment and its assemblage of microbes. Here, we use a young lineage of spiders, distributed along a chronologically arranged series of volcanic mountains, to determine the parallels between the evolutionary histories of the host spiders and their associated microbial communities, together forming the "holobiont". Using the stick spider Ariamnes waikula (Araneae, Theridiidae) on the island of Hawaii, and outgroup taxa on older islands, we tested whether each component of the holobiont (the spider hosts, the intracellular endosymbionts, and the gut microbial communities) showed correlated signatures of diversity due to sequential colonization from older to younger volcanoes. In order to investigate this, we generated ddRAD data for the host spiders and 16S rRNA gene amplicon data from their microbiota. We expected sequential colonizations to result in a (phylo)genetic structuring of the host spiders and in a diversity gradient in microbial communities. Results showed that the host A. waikula is indeed structured by geographic isolation, suggesting sequential colonization from older to younger volcanoes. Similarly, the endosymbiont communities were markedly different between Ariamnes species on different islands, but more homogeneous among A. waikula populations on the island of Hawaii. Conversely, the gut microbiota was largely conserved across all populations and species, which we suspect are generally environmentally derived. Our results highlight that the different components of the holobiont have responded in distinct ways to the dynamic environment of the volcanic archipelago, showing the necessity of understanding the interplay between components to better characterize holobiont evolution.

evolutionary biology↗

bioRxiv2020

A unified model of species abundance, genetic diversity, and functional diversity revealsthe mechanisms structuring ecological communities

Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Reconciling the relative importance of these processes is hindered by current theory, which tends to focus on a single spatial, temporal or taxonomic scale. We introduce a mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: i) species richness and abundances; ii) population genetic diversities; and iii) trait variation in a phylogenetic context. We demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. We combine our massive eco-evolutionary synthesis simulations (MESS) with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of spatial scales.

evolutionary biology↗

bioRxiv2019

Maternal stress promotes offspring growth without oxidative costs in wild red squirrels

Elevations in glucocorticoid levels (GCs) in breeding females may induce adaptive shifts in offspring life histories. Offspring produced by mothers with elevated GCs may be better prepared to face harsh environments where a faster pace of life is beneficial. We examined how experimentally elevated GCs in pregnant or lactating North American red squirrels (Tamiasciurus hudsonicus) affected offspring postnatal growth, structural size, oxidative stress levels (two antioxidants and oxidative protein damage) in three different tissues (blood, heart, liver), and liver telomere lengths. We predicted that offspring from mothers treated with GCs would grow faster but would also have higher levels of oxidative stress and shorter telomeres, which may predict reduced longevity. Offspring from mothers treated with GCs during pregnancy were 8.3% lighter around birth but grew (in body mass) 17.0% faster than those from controls, whereas offspring from mothers treated with GCs during lactation grew 34.8% slower than those from controls and did not differ in body mass around birth. Treating mothers with GCs during pregnancy or lactation did not alter the oxidative stress levels or telomere lengths of their offspring. Fast-growing offspring from any of the treatment groups did not have higher oxidative stress levels or shorter telomere lengths, indicating that offspring that grew faster early in life did not exhibit oxidative costs after this period of growth. Our results indicate that elevations in maternal GCs may induce plasticity in offspring growth without long-term oxidative costs to the offspring that might result in a shortened lifespan. Summary StatementWe show that experimental increases in glucocorticoids in breeding female North American red squirrels affects offspring postnatal growth but not levels of oxidative damage and antioxidants or telomere lengths.

evolutionary biology↗