Biology subjects

Amdam, G. V.

Publications and source records attributed to Amdam, G. V..

12 recordsLinked to original sources

bioRxiv2026

Corazonin links social role and metabolic-stress responses in honey bee workers

Corazonin is implicated in regulating diverse behavioral and physiological responses in insects, yet its role in honey bees remains unclear. Work in social and non-social species suggests an ancestral function for corazonin as a metabolic stress signal and a derived function as a pro-foraging signal in social insects. To investigate this hypothesis, we examined corazonin signaling across worker roles and metabolic states and tested its regulatory relationships with pathways central to worker division of labor. Central corazonin levels (both transcript and peptide) were approximately threefold higher in foragers than in nurses. Acute metabolic challenge did not alter brain corazonin but strongly upregulated fat body corazonin receptor (CrzR) transcript in nurses only, suggesting role-specific induction of peripheral sensitivity to corazonin signaling. Injection of synthetic corazonin decreased fat body insulin receptor substrate transcript, while transcripts of vitellogenin (Vg), unpaired-like A, ecdysone receptor B, and Cyp314a1 were unaffected. Measures of gustatory responsiveness, starvation resistance, and hemolymph sugar levels were similarly unaffected by corazonin injection. Reducing Vg through RNA interference in nurse-age bees did not affect CrzR transcript levels, despite vitellogenin's established roles in stress buffering, antioxidant defense, and lifespan. This contrast highlights the specificity of CrzR upregulation in nurses as a response to metabolic challenge rather than general stress. Together, these findings support corazonin as a co-opted nutritional signal that helps shape the forager physiological state, suggesting that it may act in part through interactions with insulin signaling rather than directly regulating classical nutritional or stress-response pathways.

zoology↗

bioRxiv2025

AI-Enhanced Marker-Assisted Selection Concept for The Multifunctional Honey Bee (Hymenoptera: Apidea) Protein Vitellogenin (Vg)

Managed honey bees (Hymenoptera: Apidae: Apis mellifera L) have experienced unsustainably high rates of annual loss driven by several interacting factors, most notably pests, pathogens, pesticides, and poor nutrition. Breeding bee stocks that can cope with these challenges is a priority. Advanced molecular methods (marker-assisted selection, MAS) have enhanced the breeding efficiency of domesticated animals in recent years, but have not contributed strongly to honey bee stock improvements. This is largely because desirable traits of bees usually emerge from collective phenotypes of workers (sterile females) instead of from the breeding individuals (queens and male drones). For collective phenotypes, single genes typically have small, additive effects, so identifying impactful MAS targets is challenging. Here, we provide proof of concept for a new approach to honey bee breeding through MAS using the multifunctional protein Vitellogenin (Vg), a protein known to interact with and mitigate the primary drivers of colony loss. Our pipeline leverages cutting-edge, artificial intelligence (AI)-driven protein structure modeling algorithms to predict the effects of genetic variants of Vg on relevant molecular functions including lipid, zinc, and DNA binding. Following the AI-powered Vg variant selection step, we use a combination of standard apicultural techniques and DNA sequencing validation to breed honey bee queens homozygous for the desirable Vg allele. Our protocol can kick-start a new area of modernized bee breeding: an AI-enhanced MAS system that allows cost-effective and nimble development of stocks to meet urgent and long-term needs of stakeholders.

genetics↗

bioRxiv2025

Assessing structure-function impacts on Vitellogenin by leveraging allelic variant occurring in honey bee subspecies Apis mellifera meliffera

Computational advances involving artificial intelligence (AI) and successful experimental state-of-the-art structure determination can provide detailed pictures of large and complex protein structures, and their variations. A standout case is Vitellogenin (Vg) derived from the honey bee (Apis mellifera). Vg is an essential protein for reproduction in almost all egg-laying animals, and can in addition regulate behavior and provide immunological support in some species, including the honey bee. Information is limited in terms of the structure-function relationships that underlie Vgs pleiotropic functions, at least in part because this protein is not expressed in the best developed gene-editing models, such as fruit flies and mice. However, naturally occurring allelic variation in Vg can provide some insight, i.e., into which changes (mutations) are allowable (present at some frequency) vs. likely not allowable (not present or only at low frequency). Here, we leverage a unique dataset of 1,086 fully sequenced Vg alleles from honey bees in 15 countries. We identify a population-specific 9 nucleotide deletion in a locally endangered honey bee subspecies (A. m. mellifera) that impacts a loop structure in a central Vg domain. Due to the A. m. mellifera population history of near extinction and human intervention, an assessment of this Vg variant is not only theoretically interesting but also relevant for subspecies conservation efforts. Using structural bioinformatics, molecular dynamics simulations, and a transformer-based indel predictor (IndeLLM), we demonstrate that Vg protein structure and stability can be maintained despite the deletion. Our approach also reveals the dynamic nature of specific regions in Vg for the first time. Generalizable results may extend to other egg-laying animals of ecological and economic importance.

bioinformatics↗

bioRxiv2025

Leveraging protein language models and scoring function for Indel characterisation and transfer learning

1.Protein language models (PLMs) are increasingly used to assess the impact of genetic variation on proteins. By leveraging sequence information alone, PLMs achieve high performance and accuracy and can outperform traditional pathogenicity predictors specifically designed to identify harmful variants contributing to diseases. PLMs can perform zero-shot inference, making predictions without task-specific fine-tuning, offering a simpler and less overfitting-prone alternative to complex methods. However, studying in-frame insertions and deletions (indels) with PLMs remains challenging. Indels alter protein length, making direct comparisons between wildtype and mutant sequences not straightforward. Additionally, indel pathogenicity is less studied than other genetic variants, such as single nucleotide variants, resulting in a lack of annotated datasets. Despite these challenges, approaches that leverage PLMs through transfer learning have emerged, making it possible to capture the features needed for more accurate predictions. Still, the current approaches are limited in terms of allowed organisms, indel length, and interpretability. In this work, we devise a new scoring approach for indel pathogenicity prediction (IndeLLM) that provides a solution for the difference in protein lengths. Our method only uses sequence information and zero-shot inference with a fraction of computing time while achieving performances similar to other indel pathogenicity predictors. We used our approach to construct a simple transfer learning approach for a Siamese network, which outperformed all tested indel pathogenicity prediction methods (Matthews correlation coefficient = 0.77). IndeLLM is universally applicable across species since PLMs are trained on diverse protein sequences. To enhance accessibility, we designed a plug-and-play Google Colab notebook that allows easy use of IndeLLM and visualisation of the impact of indels on protein sequence and structure. The tool is available on GitHub https://github.com/OriolGraCar/IndeLLM and Colab https://colab.research.google.com/drive/1CgwprttaNFR_KeJGyFzP0a0C9Y wc4P. Graphical Abstract, if needed, or logo til include on Google Colab O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/642715v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@e5d1b0org.highwire.dtl.DTLVardef@299b19org.highwire.dtl.DTLVardef@1859f02org.highwire.dtl.DTLVardef@18a7ba9_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

Ultrastructural Organization of the Honeybee Blood-Brain Barrier and Comparison with Age

The blood-brain barrier is an essential feature of the most animal nervous systems, adapted to maintain brain homeostasis across species occupying unique and dynamic environments. Understanding the structural and functional diversity of animal blood-brain barriers can aid our understanding of how this structure contributes to important areas of neuroscience such as behavior, health, and disease. The honeybee worker is a well-established model for exploring these dimensions of brain function, however, the honeybee worker blood-brain barrier has yet to be described. Here, we present the first global anatomic analysis and description of the honeybee worker blood-brain barrier and compare key ultrastructural features between two age groups. We describe the cellular makeup of the honeybee worker blood-brain barrier, patterns of heterogeneity in barrier structure throughout the brain, and highlight important areas of further study.

neuroscience↗

bioRxiv2024

Effect of aging and Varroa parasitism on the paracellular and transcellular permeability of the honeybee blood-brain barrier

Honeybees (Apis mellifera) provide crucial pollination services to agricultural systems globally, however, their healthspan in these contexts is constantly at risk. Agricultural environments impose a variety of sublethal stressors onto honeybees, including parasites, pathogens, pesticides, and poor nutrition. Synergies between age, age-associated tasks, and these stressors are believed to underlie colony failure trends of the past decade. Identifying the mechanisms by which age and stressors impact honeybee physiology is an important priority in protecting honeybee and other pollinator populations. An underexplored physiological structure in honeybees is the blood-brain barrier, a protective layer of cells that surround the brain. Here, we assess a key dimensions of blood-brain barrier function, paracellular and transcellular permeability to molecules in the hemolymph. We assess these modes of permeability in multiple age groups and after exposure to varying levels of infestation by the parasitic mite Varroa destructor during development. Our results demonstrate that the paracellular permeability of the honeybee blood-brain barrier is stable across their lifespan and upon Varroa exposure. In contrast, we found that transcellular permeability is increased in honeybees exposed to a high Varroa load. These results demonstrate how age and stress variably impact a primary protective structure of the honeybee central nervous system, which may lead to targeted interventions for protecting honeybee healthspan. The assay developed here may be easily applied to different aging- and stress contexts, further enabling studies focused on understanding maintenance and decline of the honeybee blood-brain barrier.

physiology↗

bioRxiv2024

Fat body lipogenic capacity in honey bee workers is affected by age, social role, and dietary protein

All organisms need to balance processes that consume energy against those that produce energy. With an increase in biological complexity over evolutionary time, regulation of this balance has become much more complex, resulting in specialization of metabolic tasks between organelles, cells, organs, and in the case of eusocial organisms, between the individuals who comprise the superorganism. Exemplifying this, nurse honey bees maintain high abdominal lipids, while foragers have very low lipid stores, likely contributing to efficient performance of their social role, and thus to colony fitness. The proximate mechanisms responsible for these metabolic differences remain poorly understood. Here, we investigated the effects of age, age class, and dietary macronutrients on the abdominal activity of fatty acid synthase (FAS), the enzyme responsible for de novo synthesis of fatty acids. We found that FAS activity declines as bees age past peak nursing age. Feeding both nurses and foragers carbohydrates increased FAS activity compared with starved bee, but, whether fed or starved, nurses had much higher FAS activity than similarly treated foragers, implicating reduced lipid synthesis as one component of foragers low lipid stores. Finally, we used artificial diets with different amounts of protein and fat to precociously induce low, forager-like FAS activity levels in nurse-age bees deprived of protein. We speculate that reduced protein appetite and consumption during the nurse-forager transition is responsible for suppressed lipid synthesis in foragers. Summary statementHoney bee workers show reduced fat synthesis capacity as they age and leave the nest to forage. Young bees deprived of protein have low, forager-like fat synthesis capacity.

physiology↗

bioRxiv2023

The effects of queen mandibular pheromone on nurse-aged honey bee ( Apis mellifera ) hypopharyngeal gland size and lipid metabolism

Queen honey bees (Apis mellifera) release Queen Mandibular Pheromone (QMP) to regulate traits in the caste of female helpers called workers. QMP signals the queens presence and suppresses worker reproduction. In the absence of reproduction, young workers take care of the queen and her larvae (nurse tasks), while older workers forage. In nurses, QMP increases lipid stores in abdominal fat tissue (fat body) and protein content in hypopharyngeal glands (HPG). HPG are worker-specific head glands that can synthesize royal jelly used in colony nourishment. Larger HPG signifies ability to secrete royal jelly, while shrunken glands characterize foragers that do not make jelly. While it is known that QMP increases abdominal lipid stores, the mechanism is unclear: Does QMP make workers consume more pollen which provides lipids, or does QMP increase lipogenic capacity? Here, we measure abdominal lipogenic capacity as fatty acid synthase (FAS) activity while monitoring abdominal protein content and HPG size in caged workers. Cages allow us to rigorously control worker age, pheromone exposure, and diet. In our 2-factorial design, 3-vs. 8-day-old workers (age factor) were exposed to synthetic QMP or not (pheromone factor) while consuming a lipid deficient diet. We found that QMP did not influence abdominal FAS activity or protein content, but QMP still increased HPG size in the absence of dietary lipids. Our data revealed a positive correlation between abdominal protein content and HPG size. Our findings show that QMP is not a strong modulator of lipogenic capacity in caged worker bees. However, our data may reflect that QMP mobilizes abdominal protein for production of jelly, in line with previous findings on effects of honey bee Brood Pheromone. Overall, our study expands the understanding of how QMP can affect honey bee workers. Such insights are important beyond regulatory biology, as QMP is used in various aspects of beekeeping.

physiology↗

bioRxiv2022

Identifying a developmental transition in honey bees using gene expression data

In many organisms, interactions among genes lead to multiple functional states, and changes to interactions can lead to transitions into new states. These transitions can be related to bifurcations (or critical points) in dynamical systems theory. Characterizing these collective transitions is a major challenge for systems biology. Here, we develop a statistical method for identifying bistability near a continuous transition directly from high-dimensional gene expression data. We apply the method to data from honey bees, where a known developmental transition occurs between bees performing tasks in the nest and leaving the nest to forage. Our method, which makes use of the expected shape of the distribution of gene expression levels near a transition, successfully identifies the emergence of bistability and links it to genes that are known to be involved in the behavioral transition. This proof of concept demonstrates that going beyond correlative analysis to infer the shape of gene expression distributions might be used more generally to identify collective transitions from gene expression data.

systems biology↗

bioRxiv2022

Where Honey Bee Vitellogenin may Bind Zn2+-Ions

The protein Vitellogenin (Vg) plays a central role in lipid transportation in most egg-laying animals. High Vg levels correlate with stress resistance and lifespan potential in honey bees (Apis mellifera). Vg is the primary circulating zinc-carrying protein in honey bees. Zinc is an essential metal ion in numerous biological processes, including the function and structure of many proteins. Measurements of Zn2+ suggest a variable number of ions per Vg molecule in different animal species, but the molecular implications of zinc-binding by this protein are not well understood. We used inductively coupled plasma mass spectrometry (ICP-MS) to determine that, on average, each honey bee Vg molecule binds 3 Zn2+-ions. Our full-length protein structure and sequence analysis revealed seven potential zinc-binding sites. These are located in the {beta}-barrel and -helical subdomains of the N-terminal domain, the lipid binding site, and the cysteine-rich C-terminal region of unknown function. Interestingly, two potential zinc-binding sites in the {beta}-barrel can support a proposed role for this structure in DNA-binding. Overall, our findings illustrate the capacity of honey bee Vg to bind zinc at several functional regions, indicating that Zn2+-ions are important for many of the activities of this protein. In addition to being potentially relevant for other egg-laying species, these insights provide a platform for studies of metal ions in bee health, which is of global interest due to recent declines in pollinator numbers.

biochemistry↗

bioRxiv2022

Identification of 121 variants of honey bee Vitellogenin protein sequences with structural differences at functional sites

Proteins are under selection to maintain central functions and to accommodate needs that arise in ever-changing environments. The positive selection and neutral drift that preserve functions result in a diversity of protein variants. The amount of diversity differs between proteins: multifunctional or disease-related proteins tend to have fewer variants than proteins involved in some aspects of immunity. Our work focuses on the extensively studied protein Vitellogenin (Vg), which in honey bees (Apis mellifera) is multifunctional and highly expressed and plays roles in immunity. Yet, almost nothing is known about the natural variation in the coding sequences of this protein or how amino acid-altering variants might impact structure-function relationships. Here, we map out allelic variation in honey bee Vg using biological samples from 15 countries. The successful barcoded amplicon Nanopore sequencing of 543 bees revealed 121 protein variants, indicating a high level of diversity in Vg. We find that the distribution of non-synonymous single nucleotide polymorphisms (nsSNPs) differs between protein regions with different functions; domains involved in DNA and protein-protein interactions contain fewer nsSNPs than the proteins lipid binding cavities. We outline how the central functions of the protein can be maintained in different variants and how the variation pattern may inform about selection from pathogens and nutrition.

biochemistry↗

bioRxiv2021

Screening bioactive food compounds in honey bees suggests curcumin blocks alcohol-induced damage to longevity and DNA methylation

Various bioactive food compounds may confer health and longevity benefits, possibly through altering or preserving the human epigenome. While bioactive food compounds are widely being marketed as improving health and longevity by counteracting harmful effects of poor nutrition and lifestyle, claimed effects are often not adequately documented. Using the honey bee (Apis mellifera) as a model species, we here employed a multi-step screening approach to investigate seven compounds for effects on lifespan and DNA methylation using ELISA and whole genome bisulfite sequencing (WGBS). A positive longevity effect was detected for valproic acid, isovaleric acid, and cyanocobalamin. For curcumin, we found that lifespan shortening caused by ethanol intake, was restored when curcumin and ethanol were co-administered. Furthermore, we identified region specific DNA methylation changes as a result of ethanol intake. Ethanol specific changes in DNA methylation were fully or partially blocked in honey bees receiving ethanol and curcumin together. Ethanol-affected and curcumin-blocked differentially methylated regions covered genes involved in fertility, temperature regulation and tubulin transport. Our results demonstrate fundamental negative effects of low dose ethanol consumption on lifespan and associated DNA methylation changes and present a proof-of-principle on how longevity and DNA methylation changes can be negated by the bioactive food component curcumin. Our findings provide a fundament for further studies of curcumin in mice and humans and offer an avenue to explore regarding possible prevention of health issues related to alcohol consumption.

genomics↗