Proteome Analysis of the Hemolymph, Mushroom Body, and Antenna Provides Novel Insight into Honeybee Resistance against Varroa Infestation

What proteomics has taught us about honey bee (Apis mellifera) health and disease

The Western honey bee, Apis mellifera, is currently navigating a gauntlet of environmental pressures, including the persistent threat of parasites, pathogens, and climate change - all of which compromise the vitality of honey bee colonies. The repercussions of their declining health extend beyond the immediate concerns of apiarists, potentially imposing economic burdens on society through diminished agricultural productivity. Hence, there is an imperative to devise innovative monitoring techniques for assessing the health of honey bee populations. Proteomics, recognized for its proficiency in biomarker identification and protein-protein interactions, is poised to play a pivotal role in this regard. It offers a promising avenue for monitoring and enhancing the resilience of honey bee colonies, thereby contributing to the stability of global food supplies. This review delves into the recent proteomic studies of A. mellifera, highlighting specific proteins of interest and envisioning the potential of proteomics to improve sustainable beekeeping practices amidst the challenges of a changing planet.

Bidirectional de novo peptide sequencing using a transformer model

In proteomics, a crucial aspect is to identify peptide sequences. De novo sequencing methods have been widely employed to identify peptide sequences, and numerous tools have been proposed over the past two decades. Recently, deep learning approaches have been introduced for de novo sequencing. Previous methods focused on encoding tandem mass spectra and predicting peptide sequences from the first amino acid onwards. However, when predicting peptides using tandem mass spectra, the peptide sequence can be predicted not only from the first amino acid but also from the last amino acid due to the coexistence of b-ion (or a- or c-ion) and y-ion (or x- or z-ion) fragments in the tandem mass spectra. Therefore, it is essential to predict peptide sequences bidirectionally. Our approach, called NovoB, utilizes a Transformer model to predict peptide sequences bidirectionally, starting with both the first and last amino acids. In comparison to Casanovo, our method achieved an improvement of the average peptide-level accuracy rate of approximately 9.8% across all species.

Life-history stage determines the diet of ectoparasitic mites on their honey bee hosts

Ectoparasitic mites of the genera Varroa and Tropilaelaps have evolved to exclusively exploit honey bees as food sources during alternating dispersal and reproductive life history stages. Here we show that the primary food source utilized by Varroa destructor depends on the host life history stage. While feeding on adult bees, dispersing V. destructor feed on the abdominal membranes to access to the fat body as reported previously. However, when V. destructor feed on honey bee pupae during their reproductive stage, they primarily consume hemolymph, indicated by wound analysis, preferential transfer of biostains, and a proteomic comparison between parasite and host tissues. Biostaining and proteomic results were paralleled by corresponding findings in Tropilaelaps mercedesae, a mite that only feeds on brood and has a strongly reduced dispersal stage. Metabolomic profiling of V. destructor corroborates differences between the diet of the dispersing adults and reproductive foundresses. The proteome and metabolome differences between reproductive and dispersing V. destructor suggest that the hemolymph diet coincides with amino acid metabolism and protein synthesis in the foundresses while the metabolism of non-reproductive adults is tuned to lipid metabolism. Thus, we demonstrate within-host dietary specialization of ectoparasitic mites that coincides with life history of hosts and parasites.

Expression of Molecular Markers of Resilience against Varroa destructor and Bee Viruses in Ethiopian Honey Bees (Apis mellifera simensis) Focussing on Olfactory Sensing and the RNA Interference Machinery

Varroa destructor mites and the viruses it vectors are two major factors leading to high losses of honey bees (Apis mellifera) colonies worldwide. However, honey bees in some African countries show resilience to varroa infestation and/or virus infections, although little is known about the mechanisms underlying this resilience. In this study, we investigated the expression profiles of some key molecular markers involved in olfactory sensing and RNA interference, as these processes may contribute to the bees' resilience to varroa infestation and virus infection, respectively. We found significantly higher gene expression of the odorant binding protein, OBP14, in the antennae of Ethiopian bees compared to Belgian bees. This result suggests the potential of OBP14 as a molecular marker of resilience to mite infestation. Scanning electron microscopy showed no significant differences in the antennal sensilla occurrence and distribution, suggesting that resilience arises from molecular processes rather than morphological adaptations. In addition, seven RNAi genes were upregulated in the Ethiopian honey bees and three of them-Dicer-Drosha, Argonaute 2, and TRBP2-were positively correlated with the viral load. We can conclude that the antiviral immune response was triggered when bees were experiencing severe viral infection and that this might contribute to the bees' resilience to viruses.

Tropilaelaps mercedesae Infestation Is Correlated with Injury Numbers on the Brood and the Population Size of Honey Bee Apis mellifera

Tropilaelaps mercedesae, one of the most devastating parasitic mites of honey bee Apis mellifera hosts, is a major threat to honey products by causing severe damage to honey bee colonies. Here, we recorded injury numbers caused by T. mercedesae to different body parts of the larval, pupal, and crippled adult stages of honey bee A. mellifera. We evaluated the relationship between infestation rate and injury numbers per bee for both larvae and pupae. We also noted the total bee numbers per beehive and examined the relationship between the infestation rate and population size. T. mercedesae infested all developmental stages of honey bees, with the highest injury numbers in the abdomens of bee pupae and the antennas of crippled adult bees. Although larvae received more injury numbers than pupae, both infestation rate and injury numbers decreased as the larval stage progressed to the pupal stage. The infestation rate increased as the population size per beehive decreased. This study provided new perspectives to the understanding of changes in the effects of T. mercedesae infestations on different developmental stages of honey bees. It also showed useful baseline information for screening honey bee stock that might have high defensive behaviors against mite infestation.

Critical evaluation of the use of artificial data for machine learning based de novo peptide identification

Proteins are essential components of all living cells and so the study of their in situ expression, proteomics, has wide reaching applications. Peptide identification in proteomics typically relies on matching high resolution tandem mass spectra to a protein database but can also be performed de novo. While artificial spectra have been successfully incorporated into database search pipelines to increase peptide identification rates, little work has been done to investigate the utility of artificial spectra in the context of de novo peptide identification. Here, we perform a critical analysis of the use of artificial data for the training and evaluation of de novo peptide identification algorithms. First, we classify the different fragment ion types present in real spectra and then estimate the number of spurious matches using random peptides. We then categorise the different types of noise present in real spectra. Finally, we transfer this knowledge to artificial data and test the performance of a state-of-the-art de novo peptide identification algorithm trained using artificial spectra with and without relevant noise addition. Noise supplementation increased artificial training data performance from 30% to 77% of real training data peptide recall. While real data performance was not fully replicated, this work provides the first steps towards an artificial spectrum framework for the training and evaluation of de novo peptide identification algorithms. Further enhanced artificial spectra may allow for more in depth analysis of de novo algorithms as well as alleviating the reliance on database searches for training data.

Omics-based analysis of honey bee (Apis mellifera) response to Varroa sp. parasitisation and associated factors reveals changes impairing winter bee generation

The extensive annual loss of honey bees (Apis mellifera L.) represents a global problem affecting agriculture and biodiversity. The parasitic mite Varroa destructor, associated with viral co-infections, plays a key role in this loss. Despite years of intensive research, the complex mechanisms of Varroa - honey bee interaction are still not fully defined. Therefore, this study employed a unique combination of transcriptomic, proteomic, metabolomic, and functional analyses to reveal new details about the effect of Varroa mites and naturally associated factors, including viruses, on honey bees. We focused on the differences between Varroa parasitised and unparasitised ten-day-old worker bees collected before overwintering from the same set of colonies reared without anti-mite treatment. Supplementary comparison to honey bees collected from colonies with standard anti-Varroa treatment can provide further insights into the effect of a pyrethroid flumethrin. Analysis of the honey bees exposed to mite parasitisation revealed alterations in the transcriptome and proteome related to immunity, oxidative stress, olfactory recognition, metabolism of sphingolipids, and RNA regulatory mechanisms. The immune response and sphingolipid metabolism were strongly activated, whereas olfactory recognition and oxidative stress pathways were inhibited in Varroa parasitised honey bees compared to unparasitised ones. Moreover, metabolomic analysis confirmed the depletion of nutrients and energy stores, resulting in a generally disrupted metabolism in the parasitised workers. The combined omics-based analysis conducted on strictly parasitised bees revealed the key molecular components and mechanisms underlying the detrimental effects of Varroa sp. and its associated pathogens. This study provides the theoretical basis and interlinked datasets for further research on honey bee response to biological threats and the development of efficient control strategies against Varroa mites.

Application of a Novel Hybrid CNN-GNN for Peptide Ion Encoding

Almost all state-of-the-art de novo peptide sequencing algorithms now use machine learning models to encode fragment peaks and hence identify amino acids in mass spectrometry (MS) spectra. Previous work has highlighted how the inherent MS challenges of noise and missing peptide peaks detrimentally affect the performance of these models. In the present research we extracted and evaluated the encoding modules from 3 state-of-the-art de novo peptide sequencing algorithms. We also propose a convolutional neural network-graph neural network machine learning model for encoding peptide ions in tandem MS spectra. We compared the proposed encoding module to those used in the state-of-the-art de novo peptide sequencing algorithms by assessing their ability to identify b-ions and y-ions in MS spectra. This included a comprehensive evaluation in both real and artificial data across various levels of noise and missing peptide peaks. The proposed model performed best across all data sets using two different metrics (area under the receiver operating characteristic curve (AUC) and average precision). The work also highlighted the effect of including additional features such as intensity rank in these encoding modules as well as issues with using the AUC as a metric. This work is of significance to those designing future de novo peptide identification algorithms as it is the first step toward a new approach.

Proteome analysis reveals the molecular basis of honeybee brain and midgut response to sulfoxaflor

Sulfoxaflor is a widely used pesticide in agriculture. However, the molecular effects of sublethal sulfoxaflor on honeybees (Apis mellifera L.) remain elusive. Here, the effects of a sublethal dose of sulfoxaflor (0.05 μg/bee) on the brain and midgut proteome response of the honeybee were investigated. Exposure to sublethal sulfoxaflor doses did not cause significant honeybee death, but it induced significant alterations in the brain and midgut proteomes. After sulfoxaflor challenge, 135 and 28 proteins were differentially regulated in the brain and midgut, respectively. The up-regulated proteins were mainly implicated in energy metabolism, neurotransmitter transport and drug metabolism processes, and included in particular enzymes of the citrate cycle and cellular respiration process, such as ATP citrate synthase, malate dehydrogenase, cytochrome b-c1 complex subunits, and NADH dehydrogenase. These findings suggest that honeybees enhance energy metabolism in the midgut and brain to resist sulfoxaflor challenge. Notably, treatment with sulfoxaflor resulted in a 6.8 times increase in expression levels of the major royal jelly protein 1 (MRJP1) in the brain, and knockdown of MRJP1 mRNA expression using RNA interference significantly decreased the survival rate, indicating that MRJP1 may play an important role in sulfoxaflor tolerance. Our data reveals that sulfoxaflor influences multiple processes related to both metabolism and the nervous system, and provides novel insights into the molecular basis of the honeybee brain and midgut response to sublethal dose of sulfoxaflor.

Larval exposure to parasitic Varroa destructor mites triggers specific immune responses in different honey bee castes and species

Innate immune systems are key defenses of animals and particularly important in species that lack the sophisticated adaptive immune systems as found in vertebrates. Here, we were interested to quantify variation in innate immune responses of insects in hosts that differ in their parasite susceptibility. To do this, we studied immune responses in honey bees, which can host a remarkable number of different parasites, which are major contributors of declining bee health and colony losses. The most significant parasite of honey bees is the mite Varroa destructor, which has infested the majority of global honey bee populations, and its control remains a major challenge for beekeepers. However, a number of nonmanaged honey bees seem able to control Varroa infections, for example, the Eastern honey bee Apis ceranacerana or the African honey bee Apis mellifera scutellata. These bees therefore make interesting study subjects to identify underlaying resistance traits, for example, by comparing them to more susceptible bee genotypes such as Western honey bees (A. melliferaligustica). We conducted a series of interlinked experiments and started with behavioral assays to compare the attractiveness of bee larvae to mites using different honey bee genotypes and castes. We found that 6-day-old larvae are always most attractive to mites, independently of genotype or castes. In a next step, we compared volatile profiles of the most attractive larvae to test whether they could be used by mites for host selection. We found that the abundance of volatile compounds differed between larval ages, but we also found significant differences between genotypes and castes. To further study the expected underlaying physiological differences between potentially resistant and susceptible host larvae, we compared the larval hemolymph proteomes of the three honey bee genotypes and two castes in response to mite exposure. We identified consistent upregulation of immune and stress-related genes in Varroa-exposed larvae, which differed between genotypes and castes. Tolerant honey bee castes and genotypes were characterized by stronger or more distinct immune esponses. In summary, we provide first insights into the complex involvement of the innate immune system of tolerant honey bees against mite infestations, which could be used for future breeding purposes.

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Honey bee larvae are most susceptible to mite infestations shortly before brood cell capping.

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Larval attractiveness to mites is independent of bee caste or genotype.

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Volatile compound abundance differed between genotypes, castes, and larval ages.

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Mite exposure induces specific immune and stress responses in different genotypes and castes.

Rhodnius prolixus Hemolymph Immuno-Physiology: Deciphering the Systemic Immune Response Triggered by Trypanosoma cruzi Establishment in the Vector Using Quantitative Proteomics

Understanding the development of Trypanosoma cruzi within the triatomine vector at the molecular level should provide novel targets for interrupting parasitic life cycle and affect vectorial competence. The aim of the current study is to provide new insights into triatomines immunology through the characterization of the hemolymph proteome of Rhodnius prolixus, a major Chagas disease vector, in order to gain an overview of its immune physiology. Surprisingly, proteomics investigation of the immunomodulation of T. cruzi-infected blood reveals that the parasite triggers an early systemic response in the hemolymph. The analysis of the expression profiles of hemolymph proteins from 6 h to 24 h allowed the identification of a broad range of immune proteins expressed already in the early hours post-blood-feeding regardless of the presence of the parasite, ready to mount a rapid response exemplified by the significant phenol oxidase activation. Nevertheless, we have also observed a remarkable induction of the immune response triggered by an rpPGRP-LC and the overexpression of defensins 6 h post-T. cruzi infection. Moreover, we have identified novel proteins with immune properties such as the putative c1q-like protein and the immunoglobulin I-set domain-containing protein, which have never been described in triatomines and could play a role in T. cruzi recognition. Twelve proteins with unknown function are modulated by the presence of T. cruzi in the hemolymph. Determining the function of these parasite-induced proteins represents an exciting challenge for increasing our knowledge about the diversity of the immune response from the universal one studied in holometabolous insects. This will provide us with clear answers for misunderstood mechanisms in host-parasite interaction, leading to the development of new generation strategies to control vector populations and pathogen transmission.

Suitability of drone olfactory sensitivity as a selection trait for Varroa-resistance in honeybees

The most effective strategy against brood diseases, such as those stemming from infestation by the mite Varroa destructor, is the early detection and removal of sick brood. Recent findings suggest that genes associated with worker bee olfactory perception play a central role in Varroa-sensitive hygiene (VSH). In this study, the odour sensitivity of Apis mellifera drones was examined through proboscis extension response (PER) conditioning. Individuals sensitive/insensitive to the two Varroa-parasitised-brood odours (extract-low and extract-high) were used for breeding. Twenty-one queens from a VSH-selected line (SelQ) and nineteen queens from a nonselected line (ConQ) were single-drone-inseminated with sperm from drones that showed either sensitivity (SenD+) or insensitivity (SenD-) to the two extracts. Individual VSH behaviour in a total of 5072 offspring of these combinations (SelQ × SenD+, SelQ × SenD-, ConQ × SenD+, ConQ × SenD-) was subsequently observed in a specially designed observation unit with infrared light. The results from the video observation were also separately examined, considering the genetic origin (VSH-selected or nonselected line) of the participating queens and drones. While the drone PER conditioning results were not significantly reflected in the VSH results of the respective offspring, the genetic origin of the participating queens/drones was crucial for VSH manifestation.

Queen honey bees exhibit variable resilience to temperature stress

Extreme temperature exposure can reduce stored sperm viability within queen honey bees; however, little is known about how thermal stress may directly impact queen performance or other maternal quality metrics. Here, in a blind field trial, we recorded laying pattern, queen mass, and average callow worker mass before and after exposing queens to a cold temperature (4°C, 2 h), hot temperature (42°C, 2 h), and hive temperature (33°C, control). We measured sperm viability at experiment termination, and investigated potential vertical effects of maternal temperature stress on embryos using proteomics. We found that cold stress, but not heat stress, reduced stored sperm viability; however, we found no significant effect of temperature stress on any other recorded metrics (queen mass, average callow worker mass, laying patterns, the egg proteome, and queen spermathecal fluid proteome). Previously determined candidate heat and cold stress biomarkers were not differentially expressed in stressed queens, indicating that these markers only have short-term post-stress diagnostic utility. Combined with variable sperm viability responses to temperature stress reported in different studies, these data also suggest that there is substantial variation in temperature tolerance, with respect to impacts on fertility, amongst queens. Future research should aim to quantify the variation and heritability of temperature tolerance, particularly heat, in different populations of queens in an effort to promote queen resilience.

Genetic markers for the resistance of honey bee to Varroa destructor

In the mid-20th century, the first case of infection of European bees Apis mellifera L. with the ectoparasite mite Varroa destructor was recorded. The original host of this mite is the Asian bee Apis cerana. The mite V. destructor was widespread throughout Europe, North and South America, and Australia remained the only continent free from this parasite. Without acaricide treatment any honeybee colony dies within 1–4 years. The use of synthetic acaricides has not justified itself – they make beekeeping products unsuitable and mites develop resistance to them, which forces the use of even greater concentrations that can be toxic to the bees. Therefore, the only safe measure to combat the mite is the use of biological control methods. One of these methods is the selection of bee colonies with natural mite resistance. In this article we summarize publications devoted to the search for genetic markers associated with resistance to V. destructor. The first part discusses the basic mechanisms of bee resistance (Varroa sensitive hygienic behavior and grooming) and methods for their assessment. The second part focuses on research aimed at searching for loci and candidate genes associated with resistance to varroosis by mapping quantitative traits loci and genome-wide association studies. The third part summarizes studies of the transcriptome profile of Varroa resistant bees. The last part discusses the most likely candidate genes – potential markers for breeding Varroa resistant bees. Resistance to the mite is manifested in a variety of phenotypes and is under polygenic control. The establishing of gene pathways involved in resistance to Varroa will help create a methodological basis for the selection of Varroa resistant honeybee colonies.

Varroa destructor: how does it harm Apis mellifera honey bees and what can be done about it?

Since its migration from the Asian honey bee (Apis cerana) to the European honey bee (Apis mellifera), the ectoparasitic mite Varroa destructor has emerged as a major issue for beekeeping worldwide. Due to a short history of coevolution, the host–parasite relationship between A. mellifera and V. destructor is unbalanced, with honey bees suffering infestation effects at the individual, colony and population levels. Several control solutions have been developed to tackle the colony and production losses due to Varroa, but the burden caused by the mite in combination with other biotic and abiotic factors continues to increase, weakening the beekeeping industry. In this synthetic review, we highlight the main advances made between 2015 and 2020 on V. destructor biology and its impact on the health of the honey bee, A. mellifera. We also describe the main control solutions that are currently available to fight the mite and place a special focus on new methodological developments, which point to integrated pest management strategies for the control of Varroa in honey bee colonies.

pNovo 3: precise de novo peptide sequencing using a learning-to-rank framework

MOTIVATION

De novo peptide sequencing based on tandem mass spectrometry data is the key technology of shotgun proteomics for identifying peptides without any database and assembling unknown proteins. However, owing to the low ion coverage in tandem mass spectra, the order of certain consecutive amino acids cannot be determined if all of their supporting fragment ions are missing, which results in the low precision of de novo sequencing.

RESULTS

In order to solve this problem, we developed pNovo 3, which used a learning-to-rank framework to distinguish similar peptide candidates for each spectrum. Three metrics for measuring the similarity between each experimental spectrum and its corresponding theoretical spectrum were used as important features, in which the theoretical spectra can be precisely predicted by the pDeep algorithm using deep learning. On seven benchmark datasets from six diverse species, pNovo 3 recalled 29-102% more correct spectra, and the precision was 11-89% higher than three other state-of-the-art de novo sequencing algorithms. Furthermore, compared with the newly developed DeepNovo, which also used the deep learning approach, pNovo 3 still identified 21-50% more spectra on the nine datasets used in the study of DeepNovo. In summary, the deep learning and learning-to-rank techniques implemented in pNovo 3 significantly improve the precision of de novo sequencing, and such machine learning framework is worth extending to other related research fields to distinguish the similar sequences.

AVAILABILITY AND IMPLEMENTATION

pNovo 3 can be freely downloaded from http://pfind.ict.ac.cn/software/pNovo/index.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Honey bee survival mechanisms against the parasite Varroa destructor: a systematic review of phenotypic and genomic research efforts

The ectoparasitic mite Varroa destructor is the most significant pathological threat to the western honey bee, Apis mellifera, leading to the death of most colonies if left untreated. An alternative approach to chemical treatments is to selectively enhance heritable honey bee traits of resistance or tolerance to the mite through breeding programs, or select for naturally surviving untreated colonies. We conducted a literature review of all studies documenting traits of A. mellifera populations either selectively bred or naturally selected for resistance and tolerance to mite parasitism. This allowed us to conduct an analysis of the diversity, distribution and importance of the traits in different honey bee populations that can survive V. destructor globally. In a second analysis, we investigated the genetic bases of these different phenotypes by comparing 'omics studies (genomics, transcriptomics, and proteomics) of A. mellifera resistance and tolerance to the parasite. Altogether, this review provides a detailed overview of the current state of the research projects and breeding efforts against the most devastating parasite of A. mellifera. By highlighting the most promising traits of Varroa-surviving bees and our current knowledge on their genetic bases, this work will help direct future research efforts and selection programs to control this pest. Additionally, by comparing the diverse populations of honey bees that exhibit those traits, this review highlights the consequences of anthropogenic and natural selection in the interactions between hosts and parasites.

Cuticular pheromones stimulate hygienic behavior in the honey bee (Apis mellifera)

The health of western honey bee (Apis mellifera) colonies is challenged by the parasitic mite Varroa destructor and the numerous harmful pathogens it vectors. Selective breeding for the naturally occurring social immune trait "hygienic behavior" has emerged as one sustainable approach to reducing the mites' impact on honey bees. To expand our understanding of hygienic triggers and improve hygienic selection tools, we tested the hypothesis that the cuticular compounds (Z)-10-tritriacontene and (Z)-6-pentadecene, previously associated with unhealthy honey bee brood and/or brood targeted for hygiene, are triggers of honey bee hygienic behavior independent of brood health. In support of our hypothesis, application of synthetic (Z)-10-tritriacontene and (Z)-6-pentadecene onto brood and brood cell caps significantly increased hygienic behavior compared to application of similarly structured hydrocarbon controls (Z)-16-dotriacontene and (Z)-7-pentadecene. Furthermore, we demonstrate a significant positive correlation between colony-level hygienic responses to (Z)-10-tritriacontene and the traditional freeze-killed brood assay for selection of hygienic honey bee stocks. These results confirm biological activity of (Z)-6-pentadecene and reveal (Z)-10-tritriacontene as a novel hygiene trigger. They also support development of improved tools for honey bee colony monitoring and hygienic selection, and thus may accelerate development of honey bee stocks with greater resistance to Varroa and associated pathogens.

Microglial autophagy defect causes parkinson disease-like symptoms by accelerating inflammasome activation in mice

Microglial activation-induced neuroinflammation is closely associated with the development of Parkinson disease (PD). Macroautophagy/autophagy regulates many biological processes, but the role of autophagy in microglial activation during PD development remains largely unclear. In this study, we showed that deletion of microglial Atg5 caused PD-like symptoms in mice, characterized by impairment in motor coordination and cognitive learning, loss of tyrosine hydroxylase (TH) neurons, enhancement of neuroinflammation and reduction in dopamine levels in the striatum. Mechanistically, we found that inhibition of autophagy led to NLRP3 (NLR family pyrin domain containing 3) inflammasome activation via PDE10A (phosphodiesterase 10A)-cyclic adenosine monophosphate (cAMP) signaling in microglia, and the sequential upregulation of downstream IL1B/IL-1β in turn increased the expression of MIF (macrophage migration inhibitory factor [glycosylation-inhibiting factor]), a pro-inflammatory cytokine. Inhibition of NLRP3 inflammasome activation by administration of MCC950, a specific inhibitor for NLRP3, decreased MIF expression and neuroinflammatory levels, and rescued the loss of TH neurons in the substantial nigra (SN). Interestingly, we found that serum MIF levels in PD patients were significantly elevated. Taken together, our results reveal an important role of autophagy in microglial activation-driven PD-like symptoms, thus providing potential targets for the clinical treatment of PD. Abbreviations: ATG: autophagy related; cAMP: cyclic adenosine monophosphate; cKO: conditional knockout; NOS2/INOS: nitric oxide synthase 2, inducible; IL1B: interleukin 1 beta; ITGAM/CD-11b: integrin alpha M/cluster of differentiation molecule 11B; MAP1LC3: microtubule-associated protein 1 light chain 3; MIF: macrophage migration inhibitory factor (glycosylation-inhibiting factor); NLRP3: NLR family pyrin domain containing 3; PBS: phosphate-buffered saline; PD: parkinson disease; PDE10A: phosphodiesterase 10A; SN: substantial nigra; TH: tyrosine hydroxylase; TNF: tumor necrosis factor; WT: wild type.

Insights into the feeding behaviors and biomechanics of Varroa destructor mites on honey bee pupae using electropenetrography and histology

Feeding behaviors and biomechanics of female Varroa destructor mites are revealed from AC-DC electropenetrography (EPG) recordings of mites feeding from Apis mellifera honey bee pupae and histology of mite internal ingestion apparatus. EPG signals characteristic of arthropod suction feeding (ingestion) were identified for mites that fed on pupae during overnight recordings. Ingestion by these mites was confirmed afterwards by observing internally fluorescent microbeads previously injected into their hosts. Micrographs of internal ingestion apparatus illustrate the connection between a gnathosomal tube and a pharyngeal lumen, which is surrounded by alternating dilator and constrictor muscles. Inspection of EPG signals showed the muscularized mite pharyngeal pump operates at a mean repetition rate of 4.5 cycles/s to ingest host fluids. Separate feeding events observed for mites numbered between 23 and 33 over approximately 16 h of recording, with each event lasting ~10 s. Feeding events were each separated by ~2 min. Consecutive feeding events separated by either locomotion or prolonged periods of quiescence were grouped into feeding bouts, which ranged in number from one to six. Statistical analyses of EPG data revealed that feeding events were prolonged for mites having lower pharyngeal pump frequencies, and mites having prolonged feeding events went unfed for significantly more time between feeding events. These results suggest that mites may adjust behaviors to meet limitations of their feeding apparatus to acquire similar amounts of food. Data reported here help to provide a more robust view of Varroa mite feeding than those previously reported and are both reminiscent of, as well as distinct from, some other acarines and fluid-feeding insects.

The Emerging Proteomic Research Facilitates in-Depth Understanding of the Biology of Honeybees

Advances in instrumentation and computational analysis in proteomics have opened new doors for honeybee biological research at the molecular and biochemical levels. Proteomics has greatly expanded the understanding of honeybee biology since its introduction in 2005, through which key signaling pathways and proteins that drive honeybee development and behavioral physiology have been identified. This is critical for downstream mechanistic investigation by knocking a gene down/out or overexpressing it and being able to attribute a specific phenotype/biochemical change to that gene. Here, we review how emerging proteome research has contributed to the new understanding of honeybee biology. A systematic and comprehensive analysis of global scientific progress in honeybee proteome research is essential for a better understanding of research topics and trends, and is potentially useful for future research directions.

Metabolomics-based biomarker discovery for bee health monitoring: A proof of concept study concerning nutritional stress in Bombus terrestris

Bee pollinators are exposed to multiple natural and anthropogenic stressors. Understanding the effects of a single stressor in the complex environmental context of antagonistic/synergistic interactions is critical to pollinator monitoring and may serve as early warning system before a pollination crisis. This study aimed to methodically improve the diagnosis of bee stressors using a simultaneous untargeted and targeted metabolomics-based approach. Analysis of 84 Bombus terrestris hemolymph samples found 8 metabolites retained as potential biomarkers that showed excellent discrimination for nutritional stress. In parallel, 8 significantly altered metabolites, as revealed by targeted profiling, were also assigned as candidate biomarkers. Furthermore, machine learning algorithms were applied to the above-described two biomarker sets, whereby the untargeted eight components showed the best classification performance with sensitivity and specificity up to 99% and 100%, respectively. Based on pathway and biochemistry analysis, we propose that gluconeogenesis contributed significantly to blood sugar stability in bumblebees maintained on a low carbohydrate diet. Taken together, this study demonstrates that metabolomics-based biomarker discovery holds promising potential for improving bee health monitoring and to identify stressor related to energy intake and other environmental stressors.

Stock-specific chemical brood signals are induced by Varroa and Deformed Wing Virus, and elicit hygienic response in the honey bee

The health of the honey bee Apis mellifera is challenged by the ectoparasitic mite Varroa destructor, and the numerous harmful pathogens it vectors. Existing pesticide-based Varroa controls are not sustainable. In contrast, one promising approach for improved honey bee health is the breeding of hygienic bees, capable of detecting and removing brood that is parasitized or diseased. In three experiments we find evidence to support the hypothesis that stock-specific chemical brood signals are induced by Varroa and Deformed Wing Virus, and elicit hygienic response in the honey bee. By collecting, analyzing, and running bioassays involving mite-infested and control brood extracts from three honey bee breeding stocks we: 1) found evidence that a transferrable chemical signal for hygienic behavior is present in Varroa-infested brood extracts, 2) identified ten stock-specific hydrocarbons as candidates of hygienic signaling, and 3) found that two of these hydrocarbons linked to Varroa and DWV were also elevated in brood targeted for hygienic behavior. These findings expand our understanding of honey bee chemical communication, and facilitate the development of improved hygienic selection tools to breed honey bees with greater resistance to Varroa and associated pathogens.

Honey bee predisposition of resistance to ubiquitous mite infestations

Host-parasite co-evolution history is lacking when parasites switch to novel hosts. This was the case for Western honey bees (Apis mellifera) when the ectoparasitic mite, Varroa destructor, switched hosts from Eastern honey bees (Apis cerana). This mite has since become the most severe biological threat to A. mellifera worldwide. However, some A. mellifera populations are known to survive infestations, largely by suppressing mite population growth. One known mechanism is suppressed mite reproduction (SMR), but the underlying genetics are poorly understood. Here, we take advantage of haploid drones, originating from one queen from the Netherlands that developed Varroa-resistance, whole exome sequencing and elastic-net regression to identify genetic variants associated with SMR in resistant honeybees. An eight variants model predicted 88% of the phenotypes correctly and identified six risk and two protective variants. Reproducing and non-reproducing mites could not be distinguished using DNA microsatellites, which is in agreement with the hypothesis that it is not the parasite but the host that adapted itself. Our results suggest that the brood pheromone-dependent mite oogenesis is disrupted in resistant hosts. The identified genetic markers have a considerable potential to contribute to a sustainable global apiculture.

In-depth Proteome of the Hypopharyngeal Glands of Honeybee Workers Reveals Highly Activated Protein and Energy Metabolism in Priming the Secretion of Royal Jelly

Royal jelly (RJ) is a secretion of the hypopharyngeal glands (HGs) of honeybee workers. High royal jelly producing bees (RJBs), a stock of honeybees selected from Italian bees (ITBs), have developed a stronger ability to produce RJ than ITBs. However, the mechanism underpinning the high RJ-producing performance in RJBs is still poorly understood. We have comprehensively characterized and compared the proteome across the life span of worker bees between the ITBs and RJBs. Our data uncover distinct molecular landscapes that regulate the gland ontogeny and activity corresponding with age-specific tasks. Nurse bees (NBs) have a well-developed acini morphology and cytoskeleton of secretory cells in HGs to prime the gland activities of RJ secretion. In RJB NBs, pathways involved in protein synthesis and energy metabolism are functionally induced to cement the enhanced RJ secretion compared with ITBs. In behavior-manipulated RJB NBs, the strongly expressed proteins implicated in protein synthesis and energy metabolism further demonstrate their critical roles in the regulation of RJ secretion. Our findings provide a novel understanding of the mechanism consolidating the high RJ-output in RJBs.

Proteome analysis reveals a strong correlation between olfaction and pollen foraging preference in honeybees

To gain a deeper understanding of the molecular basis of pollen foraging preference, we characterized the proteomes of antennae and brains of bees foraging on pear and rapeseed flowers, and the volatile compounds from nectar, anther, and inflorescence of both plants. Bees foraging on the pollen of the two plants have shaped the distinct proteome arsenals in the antenna and brain to drive olfactory and brain function. In antennae, bees foraging on pear (PA) pollen pathways associated with protein metabolism were induced to synthesize new proteins for modulation of synaptic structures via stabilizing and consolidating specific memory traces. Whereas, bees foraging on rapeseed (BA) pollen pathways implicated in energy metabolism were activated to provide metabolic fuels critical for neural activity. These findings suggest that the distinct biochemical route is functionally enhanced to consolidate the divergent olfaction in PA and BA. In brain, although the uniquely induced pathways in bees forging on both plants are likely to cement selective roles in learning and memory, pollen foraging preference in bees is mainly drived by olfaction. Furthermore, both plants have shaped different repertoires of signal odors and food rewards to attract pollinators. The suggested markers are potentially useful for selection of bees to improve their olfaction for better pollination of the plants.

Postnovo: Postprocessing Enables Accurate and FDR-Controlled de Novo Peptide Sequencing

De novo sequencing offers an alternative to database search methods for peptide identification from mass spectra. Since it does not rely on a predetermined database of expected or potential sequences in the sample, de novo sequencing is particularly appropriate for samples lacking a well-defined or comprehensive reference database. However, the low accuracy of many de novo sequence predictions has prevented the widespread use of the variety of sequencing tools currently available. Here, we present a new open-source tool, Postnovo, that postprocesses de novo sequence predictions to find high-accuracy results. Postnovo uses a predictive model to rescore and rerank candidate sequences in a manner akin to database search postprocessing tools such as Percolator. Postnovo leverages the output from multiple de novo sequencing tools in its own analyses, producing many times the length of amino acid sequence information (including both full- and partial-length peptide sequences) at an equivalent false discovery rate (FDR) compared to any individual tool. We present a methodology to reliably screen the sequence predictions to a desired FDR given the Postnovo sequence score. We validate Postnovo with multiple data sets and demonstrate its ability to identify proteins that are missed by database search even in samples with paired reference databases.

Quantitative proteomics reveals divergent responses in Apis mellifera worker and drone pupae to parasitization by Varroa destructor

Varroa destructor is a haemophagous ectoparasite of honeybees and is considered a major causal agent of colony losses in Europe and North America. Although originating in Eastern Asia where it parasitizes Apis cerana, it has shifted hosts to the western honeybee Apis mellifera on which it has a greater deleterious effect on the individual and colony level. To investigate this important host-parasite interaction and to determine whether Varroa causes different effects on different castes we conducted a label free quantitative proteomic analysis of Varroa-parasitized and non-parasitized drone and worker Apis mellifera pupae. 1195 proteins were identified in total, of which 202 and 250 were differentially abundant in parasitized drone and worker pupae, respectively. Both parasitized drone and worker pupae displayed reduced abundance in proteins associated with the cuticle, lipid transport and innate immunity. Proteins involved in metabolic processes were more abundant in both parasitized castes although the response in workers was more pronounced. A number of caste specific responses were observed including differential abundance of numerous cytoskeletal and muscle proteins, which were of higher abundance in parasitized drones in comparison to parasitized workers. Proteins involved in fatty acid and carbohydrate metabolism were more abundant in parasitized workers as were a large number of ribosomal proteins highlighting either potentially divergent responses to Varroa or a different strategy by the mite when parasitizing the different castes. This data improves our understanding of this interaction and may provide a basis for future studies into improvements to therapy and control of Varroasis.

The Wisdom of Honeybee Defenses Against Environmental Stresses

As one of the predominant pollinator, honeybees provide important ecosystem service to crops and wild plants, and generate great economic benefit for humans. Unfortunately, there is clear evidence of recent catastrophic honeybee colony failure in some areas, resulting in markedly negative environmental and economic effects. It has been demonstrated that various environmental stresses, including both abiotic and biotic stresses, functioning singly or synergistically, are the potential drivers of colony collapse. Honeybees can use many defense mechanisms to decrease the damage from environmental stress to some extent. Here, we synthesize and summarize recent advances regarding the effects of environmental stress on honeybees and the wisdom of honeybees to respond to external environmental stress. Furthermore, we provide possible future research directions about the response of honeybees to various form of stressors.

Recognition of mite-infested brood by honeybee (Apis mellifera) workers may involve thermal sensing

Hygienic behavior, i.e. the removal of diseased or damaged brood by worker honey bees (Apis mellifera), is seen as one of the principal behavioral elements of this species' social immunity. Identification of the stimuli that trigger it would be helpful in searching for biochemical and molecular markers of this important breeding trait. While many studies at the genomic, transcriptomic, and behavioral level have pointed to the implication of chemical cues, we here hypothesized that thermal cues are alternatively/additionally involved. To test this hypothesis, we first measured whether infestation by the mite Varroa destructor (a condition known to induce hygienic behavior) leads to a thermal gradient between affected and unaffected brood. We found that infested brood cells were between 0.03 and 0.19 °C warmer than uninfested controls. Next, we tested whether artificially heating an area of a brood comb would increase the removal of infested or uninfested brood as compared to an unheated control area, and found that this was not the case. Finally, we investigated whether the heating of individual brood cells, as opposed to comb areas, would influence brood removal from cells adjacent to the heated one. This was the case for uninfested, though not for infested cells. We conclude that infestation by V. destructor leads to a heating of brood cells that should be perceivable by bees, and that small-scale temperature gradients can influence brood removal. This makes it appear possible that thermal cues play a role in triggering hygienic behavior of honey bees directed at varroa-infested larvae/pupae, although our results are insufficient to prove such an involvement.

Proteomics Improves the New Understanding of Honeybee Biology

The honeybee is one of the most valuable insect pollinators, playing a key role in pollinating wild vegetation and agricultural crops, with significant contribution to the world's food production. Although honeybees have long been studied as model for social evolution, honeybee biology at the molecular level remained poorly understood until the year 2006. With the availability of the honeybee genome sequence and technological advancements in protein separation, mass spectrometry, and bioinformatics, aspects of honeybee biology such as developmental biology, physiology, behavior, neurobiology, and immunology have been explored to new depths at molecular and biochemical levels. This Review comprehensively summarizes the recent progress in honeybee biology using proteomics to study developmental physiology, task transition, and physiological changes in some of the organs, tissues, and cells based on achievements from the authors' laboratory in this field. The research advances of honeybee proteomics provide new insights for understanding of honeybee biology and future research directions.

A death pheromone, oleic acid, triggers hygienic behavior in honey bees (Apis mellifera L.)

Eusocial insects live in teeming societies with thousands of their kin. In this crowded environment, workers combat disease by removing or burying their dead or diseased nestmates. For honey bees, we found that hygienic brood-removal behavior is triggered by two odorants - β-ocimene and oleic acid - which are released from brood upon freeze-killing. β-ocimene is a co-opted pheromone that normally signals larval food-begging, whereas oleic acid is a conserved necromone across arthropod taxa. Interestingly, the odorant blend can induce hygienic behavior more consistently than either odorant alone. We suggest that the volatile β-ocimene flags hygienic workers' attention, while oleic acid is the death cue, triggering removal. Bees with high hygienicity detect and remove brood with these odorants faster than bees with low hygienicity, and both molecules are strong ligands for hygienic behavior-associated odorant binding proteins (OBP16 and OBP18). Odorants that induce low levels of hygienic behavior, however, are weak ligands for these OBPs. We are therefore beginning to paint a picture of the molecular mechanism behind this complex behavior, using odorants associated with freeze-killed brood as a model.

Proteomics Reveals the Molecular Underpinnings of Stronger Learning and Memory in Eastern Compared to Western Bees

The eastern (Apis cerana cerana, Acc) and western (Apis mellifera ligustica, Aml) honeybee are two major honeybee species. Surprisingly, little is known about the fundamental molecular neurobiology of brain suborgans of Acc and Aml. We characterized and compared the proteomes of mushroom bodies (MBs), antennal lobes (ALs) and optical lobes (OLs) in the brain of both species, and biologically validated the functions related to learning and memory. Acc and Aml have evolved similar proteome signatures in MBs and OLs to drive the domain-specific neural activities. In MBs of both species, commonly enriched and enhanced functional groups related to protein metabolism and Ca²⁺ transport relative to ALs and OLs, suggests that proteins and Ca²⁺ are vital for consolidating learning and memory via modulation of synaptic structure and signal transduction. Furthermore, in OLs of both species, the mainly enriched ribonucleoside metabolism suggests its vital role as second messenger in promoting phototransduction. Notably, in ALs of both species, distinct proteome settings have shaped to prime olfactory learning and memory. In ALs of Acc, this is supported by the enriched cytoskeleton organization to sustain olfactory signaling through modulation of plasticity in glomeruli and intracellular transport. In ALs of Aml, however, the enriched functional groups implicated in hydrogen ion transport are indicative of their importance in supporting olfactory processes by regulation of synaptic transmission. The biological confirmation of enhanced activities of protein metabolism and signal transduction in ALs and MBs of Acc relative to in Aml demonstrates that a stronger sense of olfactory learning and memory has evolved in Acc. The reported first in-depth proteome data of honeybee brain suborgans provide a novel insight into the molecular basis of neurobiology, and is potentially useful for further neurological studies in honeybees and other insects.

A Varroa destructor protein atlas reveals molecular underpinnings of developmental transitions and sexual differentiation

Varroa destructor is the most economically damaging honey bee pest, weakening colonies by simultaneously parasitizing bees and transmitting harmful viruses. Despite these impacts on honey bee health, surprisingly little is known about its fundamental molecular biology. Here, we present a Varroa protein atlas crossing all major developmental stages (egg, protonymph, deutonymph, and adult) for both male and female mites as a web-based interactive tool (http://foster.nce.ubc.ca/varroa/index.html). We used intensity-based label-free quantitation to find 1,433 differentially expressed proteins across developmental stages. Enzymes for processing carbohydrates and amino acids were among many of these differences as well as proteins involved in cuticle formation. Lipid transport involving vitellogenin was the most significantly enriched biological process in the foundress (reproductive female) and young mites. In addition, we found that 101 proteins were sexually regulated and functional enrichment analysis suggests that chromatin remodeling may be a key feature of sex determination. In a proteogenomic effort, we identified 519 protein-coding regions, 301 of which were supported by two or more peptides and 169 of which were differentially expressed. Overall, this work provides a first-of-its-kind interrogation of the patterns of protein expression that govern the Varroa life cycle and the tools we have developed will support further research on this threatening honey bee pest.

De novo peptide sequencing by deep learning

De novo peptide sequencing from tandem MS data is the key technology in proteomics for the characterization of proteins, especially for new sequences, such as mAbs. In this study, we propose a deep neural network model, DeepNovo, for de novo peptide sequencing. DeepNovo architecture combines recent advances in convolutional neural networks and recurrent neural networks to learn features of tandem mass spectra, fragment ions, and sequence patterns of peptides. The networks are further integrated with local dynamic programming to solve the complex optimization task of de novo sequencing. We evaluated the method on a wide variety of species and found that DeepNovo considerably outperformed state of the art methods, achieving 7.7-22.9% higher accuracy at the amino acid level and 38.1-64.0% higher accuracy at the peptide level. We further used DeepNovo to automatically reconstruct the complete sequences of antibody light and heavy chains of mouse, achieving 97.5-100% coverage and 97.2-99.5% accuracy, without assisting databases. Moreover, DeepNovo is retrainable to adapt to any sources of data and provides a complete end-to-end training and prediction solution to the de novo sequencing problem. Not only does our study extend the deep learning revolution to a new field, but it also shows an innovative approach in solving optimization problems by using deep learning and dynamic programming.

Odorant cues linked to social immunity induce lateralized antenna stimulation in honey bees (Apis mellifera L.)

Hygienic behaviour (HB) is a social immunity trait in honey bees (Apis mellifera L.) whereby workers detect, uncap and remove unhealthy brood, improving disease resistance in the colony. This is clearly economically valuable; however, the molecular mechanism behind it is not well understood. The freeze-killed brood (FKB) assay is the conventional method of HB selection, so we compared odour profiles of FKB and live brood to find candidate HB-inducing odours. Surprisingly, we found that significantly more brood pheromone (β-ocimene) was released from FKB. β-ocimene abundance also positively correlated with HB, suggesting there could be a brood effect contributing to overall hygiene. Furthermore, we found that β-ocimene stimulated worker antennae in a dose-dependent manner, with the left antennae responding significantly stronger than right antennae in hygienic bees, but not in non-hygienic bees. Five other unidentifiable compounds were differentially emitted from FKB which could also be important for HB. We also compared odour profiles of Varroa-infested brood to healthy brood and found an overall interactive effect between developmental stage and infestation, but specific odours did not drive these differences. Overall, the data we present here is an important foundation on which to build our understanding the molecular mechanism behind this complex behaviour.