Biology subjects

Antonelli, A.

Publications and source records attributed to Antonelli, A..

At least 19 recordsLinked to original sources

bioRxiv2026

The diversity, evolution, and conservation of African plants

Africa hosts remarkable biodiversity across diverse biomes, yet its evolutionary history at continental-scale remains poorly understood. We integrate a time-calibrated phylogeny covering 93% of African vascular plant genera with continental-scale distribution data to jointly evaluate phylogenetic diversity (PD), endemism, and diversification rates (DR). We reveal a pronounced decoupling between DR and accumulated evolutionary history across Africa. Mountain, arid, and semi-arid areas emerge as centers of neo-endemism and elevated diversification, whereas lowland and humid regions, particularly the Guineo-Congolian zone, are dominated by older lineages with low recent diversification. Several DR hotspots do not overlap with Global Biodiversity Hotspots, indicating a mismatch between rapid diversification and accumulated evolutionary history. High net diversification and speciation rates during the last 15 million years were likely driven by cooling, aridification, and mountain uplift that created new ecological gradients and isolation barriers. These abiotic changes, interacting with lineage-specific traits, shaped African modern flora and highlight conservation gaps, especially in arid regions

evolutionary biology↗

bioRxiv2026

Integrated metabolic and proteostatic profiling reveals remodeling of proteolytic pathways associated with redox-bioenergetic dysfunction in a PAHenu2 mouse model of phenylketonuria

Phenylketonuria (PKU) is a genetic metabolic disorder caused by the lack of functional phenylalanine hydroxylase (PAH). Elevated levels of phenylalanine (Phe) are known to be neurotoxic; however, the molecular mechanisms underlying Phes effects remain elusive. This study investigates the impact of PKU on proteostasis, redox balance, and metabolism in BTBR PAHenu2 mice, a severe disease animal model. Combined proteomics and metabolomics revealed impaired redox homeostasis in the brain and disrupted mitochondrial energy metabolism (ATP and TCA intermediates). The dysregulation was further supported by decreased levels of ATP, reduced glutathione (GSH), cysteine, and reduced catalase activity. Western blot analyses revealed substantial remodeling of protein degradation systems: the 19S regulatory (Rpt1) subunit and 26S proteasome content and activity were significantly increased, and ubiquitinated protein levels were elevated, indicating protein turnover and activation of the ubiquitin-proteasome system. Autophagy was also activated, as evidenced by a reduced LC3-II/LC3-I ratio, decreased p62 levels, unchanged ATG5 levels, and increased HSPA8 protein expression. By contrast, UPR markers remained stable despite an increase in the oxidized-to-reduced PDI ratio, suggesting a localized shift without activation of a full ER stress response. In parallel, systemic alterations were assessed in whole blood. Indeed, GSH, cysteine, ATP and ADP were decreased in PKU, whereas NADPH increased. These changes were accompanied by reduced activities of GSH reductase and GSH peroxidase, thereby confirming metabolic and redox disruption. Collectively, these findings indicate that PKU is associated with activation of protein degradation pathways as an adaptive response to cellular stress combined with redox imbalance and energy dysregulation. Highlights- Proteasome complex levels and activity were upregulated in PAHenu2 mouse brains - Autophagy was also enhanced in PAHenu2 mouse brains - Despite increased PDI oxidation, the Unfolded Protein Response was not activated - Redox and energy metabolism were disrupted in both brain and blood

molecular biology↗

bioRxiv2026

Dissetangling the Vine: Phylogenomics and Historical Biogeography of Vanilla (Orchidaceae)

Renowned for its aromatic fruits and economic importance, the genus Vanilla poses longstanding taxonomic and phylogenetic challenges. Despite recent molecular studies, a comprehensive species tree is lacking, and the evolutionary processes and historical patterns shaping the genus remain poorly understood. We present a new, comprehensive phylogenomic framework for Vanilla, based on 349 low-copy nuclear genes and 76 plastid loci from the Angiosperms353 probe set, which we used to infer evolutionary relationships, assess cyto-nuclear and gene-species tree discordance, and thoroughly investigate its historical distribution and diversification. Sampling 43% of the genus, our framework resolves phylogenetic uncertainties, clarifies major clades, confirms prior hypotheses, and reveals novel placements, including V. planifolia and Vanilla subg. Gondwana. Discordances are primarily driven by incomplete lineage sorting, particularly in the vanillin-producing clade, with evidence of both ancient and recent hybridization, including a natural hybrid from the Yucatan Peninsula. Biogeographic analyses indicate a Guiana Shield origin ([~]30 Mya), Amazonia as a major diversification source, the Andes as a permeable barrier, and Central America as the main diversification sink. This study provides a robust evolutionary framework for Vanilla, supporting taxonomic revisions, comparative trait analyses, and a deeper understanding of the processes shaping this economically and biologically important orchid genus.

evolutionary biology↗

bioRxiv2025

Environmental Variation Promotes Convergent Evolution and Rapid Diversification of Wing Shape and Color in Skipper Butterflies

Predation is a key driver of speciation and phenotypic diversification, yet how antipredator traits evolve and persist over evolutionary time remains poorly understood. We generated target sequence capture and whole-genome sequencing data for the skipper butterfly subfamily Eudaminae (Hesperiidae) to test whether antipredator defenses, in interaction with environmental variation, promote diversification. We focus on two antipredation wing traits: hindwing tails, which deflect predator attacks, and blue-green coloration, which may enhance motion dazzle and be used as warning coloration. Applying phylogenomics, morphometrics, and comparative methods, we model trait evolution in relation to diel activity and geographic distribution and find that hindwing tails repeatedly evolved at least seven times and blue-green coloration at least fifteen times. Both traits are associated with elevated speciation rates, but evolutionary transitions toward tailless wings and non-iridescent coloration occurred more frequently than trait gains, indicating high evolutionary lability of these antipredator defenses. Trait loss, particularly pronounced in tropical diurnal species, may reflect trade-offs in flight performance, shifts in predation guilds, or the evolution of alternative defensive traits. Our findings highlight rampant convergent evolution of wing traits that are under strong predator-mediated selection. By identifying how antipredator defenses and environmental contexts influence phenotypic and species diversification, this study provides new insights into the ecological and evolutionary processes underlying insect diversity.

evolutionary biology↗

bioRxiv2025

Setting priorities for the acquisition of primary plant occurrence data

AimEffective implementation of the Global Biodiversity Framework and Global Strategy for Plant Conservation depends on accurate species distribution data. Current vascular plant distribution data, while crucial for understanding terrestrial ecosystems, is often sparse and biased and requires significant expansion. This study developed a scalable approach to prioritize areas for plant occurrence data acquisition, adaptable to national priorities and providing a framework for botanical institutions to coordinate efforts and allocate resources. LocationGlobal. MethodsUsing a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) analysis, we prioritized areas based on: (a) ecosystem service value; (b) floristic value threatened by climate or land-use change; and (c) uncertainty in species richness estimates, stratified by biome and region. Regional prioritization maps for Africa & Madagascar; East, South and Southeast Asia; Siberia and the Russian Far East; South America; and North & Central America were reviewed by botanical experts for validation. Scalability was assessed by comparing regional and global analyses. ResultsData-driven priority maps, divided into tree-dominated and grassland/deforested areas, largely received expert support. High similarity between global and regional maps demonstrated scalability. Main conclusionsOur approach provides a framework for supporting national implementation of the Global Biodiversity Framework. Variables and their weights can be tailored to national or local needs. The methods flexibility and adaptability extend to other taxonomic groups and objectives, such as protected area selection By prioritizing data acquisition, whether field-based or digital, this research promotes the efficient use of resources. A key advantage of this approach is its capacity to systematically translate expert opinion into explicit and quantitative criteria, which in turn facilitates clear communication with policymakers and funders.

plant biology↗

bioRxiv2025

Predictive in vitro profiling of LNP-induced innate immune response using an iPSC-derived monocyte model

Lipid nanoparticles (LNPs) are a powerful drug delivery platform advancing vaccines and gene therapies. While their efficacy and safety has been found to be closely linked to innate immune activation, current in vitro models are unable to predict immune responses reliably. Conventional models, such as PBMCs, are limited by donor variability and inconsistent sensitivity. To address this, we developed a cytokine profiling platform using induced pluripotent stem cell (iPSC)-derived monocytes (iMonocytes), a physiologically relevant innate immune cell type that plays a key role in immune surveillance and inflammation. iPSCs provide a renewable, uniform monocyte source for consistent, high-sensitivity LNP screening. When tested with LNPs of graded immunostimulatory potency, iMonocytes showed improved reproducibility and strong correlation with in vivo cytokine responses. This platform enables evaluation of cargo- and dose-dependent effects, providing a robust and scalable tool for preclinical assessment and rational design of LNP therapeutics.

bioengineering↗

bioRxiv2025

A single MHCII neoepitope mRNA vaccine elicits CD4 T- and B- cell responses promoting endogenous CD8 anti-tumor immunity

Recent progress in therapeutic cancer vaccines has shown promising clinical activity, especially when targeting MHC class I (MHCI) neoantigen-specific CD8+ T cell responses in post-surgical patients. To explore the role of CD4+ T cells in vaccine-dependent tumor rejection, we constructed an mRNA lipoplex vaccine encoding a single MHCII-restricted neoantigen. The vaccine elicited Tfh and Th1 cell responses while decreasing Tregs, leading to rejection of established tumors in mice. IL-21 and IFN-{gamma}, crucial for Tfh and Th1 function respectively, contributed to anti-tumor activity. B cells and neoantigen-specific antibodies were also shown to participate in vaccine efficacy. Additionally, conventional type 1 dendritic cells (cDC1s) were essential for eliciting vaccine-induced CD4+ T cells, and both cDC1s and CD4+ T cells were required to enhance endogenous CD8+ responses, which were crucial for tumor control. Our results suggest that immunizing against MHCII neoantigens alone is sufficient to orchestrate a potent and cooperative immune response against cancer.

immunology↗

bioRxiv2025

Predicting Ecosystem Resilience Using Multi-Agent Reinforcement Learning

Twin models of natural ecosystems hold great promise for informing real-world decisions on sustainable land use and biodiversity conservation. However, existing simulations of animal behavior often rely on manually crafted rules, limiting their scalability and practical utility. Here, we present a flexible and scalable agent-based modeling approach that uses reinforcement learning--instead of hand-coded rules--to simulate animal behavior. We validate this approach across ten alpine ecosystems featuring wolves, chamois, and vegetation. By comparing model outputs with empirical data, we show that the simulations reproduce realistic ecological and behavioral patterns, including population dynamics, life history traits, and social interactions. We then use the model to assess ecosystem resilience under scenarios of habitat degradation, game hunting, and heat stress. Our framework paves the way for realistic simulations advancing our ability to predict ecosystem responses to disturbance and tipping points leading to biodiversity loss, in order to support conservation planning and guide the sustainable use of natural resources.

ecology↗

bioRxiv2025

AI-based prediction of herbarium sequencing success across the plant tree of life

DNA recovered from herbarium specimens represents a vital asset in botanical research, playing a pivotal role in unravelling the evolution, diversity, and ecological dynamics of plants. Despite its importance, challenges such as fragmented DNA and insufficient sequencing yields render molecular data retrieval a high-risk and costly endeavour involving the use of non-replaceable herbarium specimens. Here, we propose a framework based on Artificial Intelligence (AI) to forecast the success of genomic DNA extraction suitable for sequencing from herbarium samples. Our model integrates morphological characteristics and sample colour derived from scanned herbarium images, metadata including sample age and locality, and DNA quantity measurements of samples. We train a deep learning algorithm with ca. 2,000 specimens that have been digitized and sequenced in the framework of the Plant and Fungal Trees of Life (PAFTOL) Project, spanning from year 1832 to the present. As training datasets increase with ongoing digitization and genomic sequencing efforts, our AI predictive model can support researchers in selecting the herbarium samples with the highest likelihood of yielding high-quality genomic DNA from amongst a vast array of globally distributed candidate specimens. Our approach enhances the contribution of herbarium-derived DNA in large-scale studies and facilitates the utilisation of historical collections for a deeper understanding of plant evolution and ecology, with implications for conservation.

plant biology↗

bioRxiv2025

Using artificial intelligence to optimize ecological restoration for climate and biodiversity

The restoration of degraded ecosystems is critical for mitigating climate change and reversing biodiversity loss. Depending on the primary objective - such as maximizing carbon sequestration or protecting threatened species - and within the boundaries of budget constraints, different spatial priorities have been identified at global and regional scales. Funding mechanisms to support such work comprise public sources, philanthropy, and the private sector, including the sales of carbon and biodiversity credits. However, effectively exploring tradeoffs among restoration objectives and estimating the price of biodiversity and carbon credits to design financially viable projects remain challenging. Here we harness the power of artificial intelligence in our software CAPTAIN, which we further develop to identify spatial priorities for ecological restoration that maximize multiple objectives at once and to allow a robust evaluation of biodiversity and climate outcomes. We find through a series of simulations that even low-to-moderate consideration of biodiversity in restoration projects leads to the selection of restored areas that disproportionately improve the conservation of threatened species, while resulting in a relatively smaller total amount of carbon captured. We propose a data-driven valuation of biodiversity credits in relation to carbon credits, enabling the design of a bundled financial model that could support restoration efforts even in areas previously excluded for economic reasons. Applying our methodology to plant diversity in the Atlantic Forest of eastern South America, one of the most biodiverse and threatened ecosystems globally, we demonstrate its practical utility in guiding real-world restoration and quantifying the essential trade-offs between climate and nature outcomes. Our study provides a robust, scalable methodological pathway to optimize the outcomes of restoration efforts for climate and nature.

bioinformatics↗

bioRxiv2023

Morphometrics and phylogenomics of coca (Erythroxylum spp.) illuminate its reticulate evolution, with implications for taxonomy

South American coca (Erythroxylum coca and E. novogranatense) has been a key-stone crop for many Andean and Amazonian communities for at least 8,000 years. However, over the last half century, global demand for cocaine has placed this plant in the centre of armed conflict, deforestation, and explosive growth of illegal economies. While national and international agencies progress from a war on drugs policy model towards locally appropriate, data-informed strategies to tackle coca plantations, monitoring their expansion and composition remains essential. The principal means to identify coca plants is leaf morphology, yet the extent to which it is reflected in taxonomy is uncertain. Here, we analyse the consistency of the current naming system of coca and its four closest wild relatives (the coca clade), using morphometrics, phylogenomics, and population genomics. We include the name-bearing type specimens of cocas closest wild relatives E. gracilipes and E. cataractarum. Morphometrics of 342 digitized herbarium specimens show that leaf shape and size fail to reliably discriminate between species and varieties. However, the rounder and more obovate leaves of certain coca varieties could be associated with domestication syndrome of this crop. Our phylogenomic data indicate gene flow involving monophyletic clades of E. gracilipes and the E. coca clade. These results further clarify the evolution of coca and support a taxonomic framework wherein E. gracilipes is retained as a single species. Our findings have implications for the development of cost-effective genotyping methods to effectively discriminate varieties of cultural significance from high-yielding cultivars fuelling the lucrative cocaine market.

plant biology↗

bioRxiv2023

Plant diversity darkspots for global collection priorities

O_LIMore than 15% of all vascular plant species may remain scientifically undescribed, and many of the >340,000 described species have no or few geographic records documenting their distribution. Identifying and understanding taxonomic and geographic knowledge shortfalls is key to prioritising future collection and conservation efforts. C_LIO_LIUsing extensive data for 343,523 vascular plant species and time-to-event analyses, we conducted multiple tests related to plant taxonomic and geographic data shortfalls, and identified 32 global diversity darkspots (regions predicted to lack most information about their species diversity and distribution). We defined priority regions for future collection according to several socio-economic and environmental scenarios. C_LIO_LIMost plant diversity darkspots are found within biodiversity hotspots, except New Guinea. We identify New Guinea, the Philippines, Borneo, Myanmar, India, Turkey, Colombia, Ecuador, and Peru, as global collection priorities under all environmental and socio-economic conditions considered. C_LIO_LIOur study provides a framework to accelerate plant species documentation for the implementation of conservation actions. As digitisation of the worlds herbaria progresses, collection and conservation priorities may soon be identifiable at finer scales. C_LI

plant biology↗

bioRxiv2023

Spiny but photogenic: amateur sightings complement herbarium specimens to reveal the bioregions of cacti

PremiseCacti are characteristic elements of the Neotropical flora and of major interest for biogeographic, evolutionary, and ecological studies. Here we test global biogeographic boundaries for Neotropical Cactaceae using specimen-based occurrences coupled with data from visual observations, including citizen science records, as a means to tackle the known collection biases in the family. MethodsSpecies richness and record density were assessed separately for preserved specimens and human observations and a bioregional scheme tailored to Cactaceae was produced using the interactive web application Infomap Bioregions based on data from 261,272 point records cleaned through automated and manual steps. Key ResultsWe find that areas in Mexico and southwestern USA, Eastern Brazil and along the Andean region have the greatest density of records and the highest species richness. Human observations complement information from preserved specimens substantially, especially along the Andes. We propose 24 cacti bioregions, among which the most species-rich are, in decreasing order: northern Mexico/southwestern USA, central Mexico, southern central Mexico, Central America, Mexican Pacific coast, central and southern Andes, northwestern Mexico/extreme southwestern USA, southwestern Bolivia, northeastern Brazil, Mexico/Baja California. ConclusionsThe bioregionalization proposed shows novel or modified biogeographical boundaries specific to cacti, and can thereby aid further evolutionary, biogeographic, and ecological studies by providing a validated framework for further analyses. This classification builds upon, and is distinctive from, other expert-derived regionalization schemes for other taxa. Our results showcase how observation data, including citizen-science records, can complement traditional specimen-based data for biogeographic research, particularly for taxa with specific specimen collection and preservation challenges and those that are threatened or internationally protected.

plant biology↗

bioRxiv2022

Large-scale assessment of habitat quality and quantity change on declining European butterflies

The rapid decline of biodiversity as a consequence of increased environmental impact by human activities requires urgent action against the ongoing crisis. At the heart of conservation policy is the debate on quality versus quantity: should the post-2020 Global Biodiversity Framework focus on maximising total protected area, or pursue instead qualitative targets? To improve conservation practices, we need to both understand the current trend of biodiversity and the factors driving the decline. We address this by: (1) projecting current European butterfly population trends for the next 50 and 100 years, (2) comparing the decline in species richness, phylogenetic diversity and habitat specialization among different habitats, and (3) estimating the relationship between recent trends in habitat quality or quantity and the decline of multiple metrics of European butterfly diversity. We do not find any significant relationship between diversity loss and habitat area loss and conclude that neither long-term nor short-term changes in habitat area are primary predictors of large-scale butterfly decline in Europe. Habitat quality emerges as the most crucial factor in our analyses - both the area affected and the severity of habitat quality reduction. Habitat degradation causes vegetation changes in structure and diversity, which affect butterfly survival. We also estimate a higher decline of habitat specialists than generalist species. We conclude that habitat protection cannot focus solely on the maximization of habitat area but urgently needs to restore high quality ecosystems to provide the full range of ecological requirements for biodiversity.

ecology↗

bioRxiv2022

Two major extinction events in the evolutionary history of turtles: one caused by a meteorite, the other by hominins

We live in a time of highly accelerated extinction, which has the potential to mirror past mass extinction events. However, the rarity of these events and the restructuring of diversity that they cause complicate direct comparisons between the current extinction crisis and earlier mass extinctions. Among animals, turtles (Testudinata) are one of few groups which both have a sufficient fossil record and a sufficiently stable ecological importance to enable meaningful comparisons between the end Cretaceous mass extinction and the ongoing extinction event. In this paper we analyze the fossil record of turtles and recover three significant peaks in extinction rate. Two of these are in the Cretaceous, the second of these took place at the Cretaceous-Paleogene transition (K-Pg), reflecting the overall patterns previously reported for many other taxa. The third major extinction event started in the Pliocene and continues until now. This peak only affected terrestrial turtles and started much earlier in Eurasia and Africa lineages than elsewhere. This suggests that it may be linked to co-occurring hominins rather than having been caused by global climate change.

evolutionary biology↗

bioRxiv2022

A call for improving the Key Biodiversity Areas framework

Eight percent of all land surface has been designated as "Key Biodiversity Areas" (KBAs). Since these areas were established based on only two percent of all terrestrial species estimated to exist, we ask what would happen if we used all species on Earth to identify additional KBAs. We explore this question at a global scale by using data from 64,110 species of animals and plants to identify how many areas could qualify as KBAs under current criteria. We find that between 26% and 68% of the worlds terrestrial areas can be classified as KBAs, depending on the spatial resolution. The total area from potential KBAs increases drastically as more species are assessed, suggesting that if all species were included, virtually all land surface could eventually meet the biological requirements for becoming a KBA. In addition, KBAs lack a data-driven ranking system, thus assuming that all KBAs are equally worthy protection. KBAs are intended to be areas which are both of biological importance and manageable but the current approach largely sidesteps the biological component. We make an urgent call for stricter criteria in the KBA methodology or alternative methodologies that allow for biologically robust area prioritization, help secure evidence-based investments, and support progress towards the targets under the new Global Biodiversity Framework.

ecology↗

bioRxiv2022

Museomic approaches to genotype historic Cinchona barks

Over the last few centuries, millions of plant specimens have been collected and stored within herbaria and biocultural collections. They therefore represent a considerable resource for a broad range of scientific uses. However, collections degrade over time, and it is therefore increasingly difficult to characterise their genetic signatures. Here, we genotyped highly degraded Cinchona barks and leaves from herbaria using two separate high-throughput sequencing methods (HtS) and compared their performance. We subsequently genotyped specimens using genome skimming, the most commonly performed high-throughput sequencing (HtS) technique. We additionally used a recently developed capture bait set (Angiosperm353) for a target enrichment approach. Specifically, phylogenomic analyses of modern leaf and historical barks of Cinchona were performed, including 23 historical barks and six fresh leaf specimens. We found that samples degraded over time, which directly reduced the quantity and quality of the data produced by both methodologies (in terms of reads mapped to the references). However, we found that both approaches generated enough data to infer phylogenetic relationships, even between highly degraded specimens that are over 230 years old. However, the target capture kit produced data for target nuclear loci and also chloroplast data, which allowed for phylogenies to be inferred from both genomes, whereas it was only possible to use chloroplast data using genome skimming. We therefore find the Angiosperms353 target capture kit a powerful alternative to genome skimming, which can be used to obtain more information from herbarium specimens, and ultimately additional cultural benefits.

genomics↗

bioRxiv2022

Building a novel nuclear-organelle genomic framework for the fever tree (Cinchona pubescens Vahl) through short and long-read DNA data assemblies

BackgroundThe Andean Fever tree (Cinchona L.; Rubiaceae) is the iconic source of bioactive quinine alkaloids, which have been vital to treating malaria for centuries. C. pubescens Vahl, in particular, has been an essential source of income for several countries within its native range in north-western South America. However, an absence of available genomic resources is essential for placing the Cinchona species within the tree of life and setting the foundation for exploring the evolution and biosynthesis of quinine alkaloids. FindingsWe address this gap by providing the first highly contiguous and annotated nuclear and organelle genome assemblies for C. pubescens. Using a combination of [~]120 Gb of long sequencing reads derived from the Oxford Nanopore PromethION platform and 142 Gb of short-read Illumina data. Our nuclear genome assembly comprises 603 scaffolds comprising a total length of 904 Mb, and the completeness represents [~]85% of the genome size (1.1 Gb/1C). This draft genome sequence was complemented by annotating 72,305 CDSs using a combination of de novo and reference-based transcriptome assemblies. Completeness analysis revealed that our assembly is moderately complete, displaying 83% of the BUSCO gene set and a small fraction of genes (4.6%) classified as fragmented. Additionally, we report C. pubescens plastome with a length of [~]157 Kb and a GC content of 37.74%. We demonstrate the utility of these novel genomic resources by placing C. pubescens in the Gentianales order using additional plastid and nuclear datasets. ConclusionsOur study provides the first genomic resource for C. pubescens, thus opening new research avenues, including the provision of crucial genetic resources for analysis of alkaloid biosynthesis in the Fever tree.

bioinformatics↗