Honey Bee Populations Research Articles

Molecular investigation and infection patterns of seven viruses of honey bee (Apis mellifera L, 1758) populations from southeastern Morocco

An epidemiological survey of honey bee viruses was conducted on 87 clinically healthy beehives located in southeastern Morocco. The sampled colonies were analyzed by reverse transcriptase (RT)-PCR / Real Time RT-qPCR with the aim of detecting and / or quantifying the following viruses: acute bee paralysis virus (ABPV), chronic bee paralysis virus (CBPV), deformed wing virus (DWV), sacbrood virus (SBV), black queen cell virus (BQCV), Kashmir bee virus (KBV) and Israeli acute paralysis virus (IAPV). With the exception of the last two of these viruses, all the other five were detected with different prevalence rates. DWV showed the highest prevalence rate (89.65%), followed by BQCV (17.24%), ABPV (8.04%), CBPV (4.59%), and SBV (2.29%). This study represents the first molecular detection of BQCV in the country. Among all investigated colonies, only eight were virus free (9.2%). By contrast, single infection was detected in 64.37% of colonies, 21.8% showed mixed infection with two viruses, while 4.6% showed three. Nucleotide sequences of a portion of the DWV polyprotein gene obtained for six honey bee samples showed the greatest nucleotide identity with sequences of DWV from Sweden and Ireland. The negative effect of migratory beekeeping as opposed to stationary beekeeping was highlighted given that stationary beehives showed infection with up to three viruses only, while migratory beehives showed up to five viruses. The results of this study are of crucial importance as they shed light on the current status of honey bee health in southeastern Morocco.

Varroa destructor shapes the unique viral landscapes of the honey bee populations of the Azores archipelago.

The worldwide dispersal of the ectoparasitic mite Varroa destructor from its Asian origins has fundamentally transformed the relationship of the honey bee (Apis mellifera) with several of its viruses, via changes in transmission and/or host immunosuppression. The extent to which honey bee-virus relationships change after Varroa invasion is poorly understood for most viruses, in part because there are few places in the world with several geographically close but completely isolated honey bee populations that either have, or have not, been exposed long-term to Varroa, allowing for separate ecological, epidemiological, and adaptive relationships to develop between honey bees and their viruses, in relation to the mite's presence or absence. The Azores is one such place, as it contains islands with and without the mite. Here, we combined qPCR with meta-amplicon deep sequencing to uncover the relationship between Varroa presence, and the prevalence, load, diversity, and phylogeographic structure of eight honey bee viruses screened across the archipelago. Four viruses were not detected on any island (ABPV-Acute bee paralysis virus, KBV-Kashmir bee virus, IAPV-Israeli acute bee paralysis virus, BeeMLV-Bee macula-like virus); one (SBV-Sacbrood virus) was detected only on mite-infested islands; one (CBPV-Chronic bee paralysis virus) occurred on some islands, and two (BQCV-Black queen cell virus, LSV-Lake Sinai virus,) were present on every single island. This multi-virus screening builds upon a parallel survey of Deformed wing virus (DWV) strains that uncovered a remarkably heterogeneous viral landscape featuring Varroa-infested islands dominated by DWV-A and -B, Varroa-free islands naïve to DWV, and a refuge of the rare DWV-C dominating the easternmost Varroa-free islands. While all four detected viruses investigated here were affected by Varroa for one or two parameters (usually prevalence and/or the Richness component of ASV diversity), the strongest effect was observed for the multi-strain LSV. Varroa unambiguously led to elevated prevalence, load, and diversity (Richness and Shannon Index) of LSV, with these results largely shaped by LSV-2, a major LSV strain. Unprecedented insights into the mite-virus relationship were further gained from implementing a phylogeographic approach. In addition to enabling the identification of a novel LSV strain that dominated the unique viral landscape of the easternmost islands, this approach, in combination with the recovered diversity patterns, strongly suggests that Varroa is driving the evolutionary change of LSV in the Azores. This study greatly advances the current understanding of the effect of Varroa on the epidemiology and adaptive evolution of these less-studied viruses, whose relationship with Varroa has thus far been poorly defined.

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.

Analysis of Varroa Mite Colony Infestation Level Using New Open Software Based on Deep Learning Techniques.

Varroa mites, scientifically identified as Varroa destructor, pose a significant threat to beekeeping and cause one of the most destructive diseases affecting honey bee populations. These parasites attach to bees, feeding on their fat tissue, weakening their immune systems, reducing their lifespans, and even causing colony collapse. They also feed during the pre-imaginal stages of the honey bee in brood cells. Given the critical role of honey bees in pollination and the global food supply, controlling Varroa mites is imperative. One of the most common methods used to evaluate the level of Varroa mite infestation in a bee colony is to count all the mites that fall onto sticky boards placed at the bottom of a colony. However, this is usually a manual process that takes a considerable amount of time. This work proposes a deep learning approach for locating and counting Varroa mites using images of the sticky boards taken by smartphone cameras. To this end, a new realistic dataset has been built: it includes images containing numerous artifacts and blurred parts, which makes the task challenging. After testing various architectures (mainly based on two-stage detectors with feature pyramid networks), combination of hyperparameters and some image enhancement techniques, we have obtained a system that achieves a mean average precision (mAP) metric of 0.9073 on the validation set.

“What’s Good for the Bees Will Be Good for Us!”—A Qualitative Study of the Factors Influencing Beekeeping Activity

Beekeepers play a crucial role in the survival of honey bee populations, so it is essential to understand the drivers behind their activities. This qualitative study aims to explore the factors influencing beekeepers’ decision-making and to assess the relationship between beekeepers and their bees, to identify the relationship between them by building a theoretical model, and to assess the perception of pollination services as a potential source of income diversification among Hungarian beekeepers. Based on the grounded theory method, we created a paradigm model of beekeeping management based on semi-structured interviews with beekeepers in Hungary. In the analysis of the interviews, we first used open coding to develop categories according to the concepts used by the beekeepers, and then structured and linked these categories (axial coding). Finally, we identified the most relevant main categories (selective coding) and outlined the conceptual framework for beekeeping management. We mapped the strategies and beekeeping practices beekeepers use and the consequences they generate. The results show that several causal conditions influence beekeeping decisions and strategies. In an environment where beekeepers’ costs are increasing and their incomes are decreasing while implementing adaptation strategies, more targeted measures are needed to protect bees and increase beekeepers’ profitability.

Occurrence of Lotmaria Passim in Africanized and European Honey Bee, Apis Mellifera, Lineages from the United States

Abstract Honey bee populations in the United States have been under stress for the past several decades. Several internal parasites may contribute to this, including the trypanosome Lotmaria passim. It is unknown how widespread the honey bee parasite, L. passim, is in Africanized honey bee (AHB) populations in the United States. A total of 321 feral honey bee colony samples which had been previously recorded to be of Africanized origin using molecular diagnostics from California (n=3), New Mexico (n=46), Oklahoma (n=57), Texas (n=106), and Utah (n=109) were used in this study. Of these samples, a total of 15 (4.7%) from three States were positive for L. passim. Utah AHB samples had the highest infection rate (11.0%), followed by Texas (1.9%) and Oklahoma (1.8%). Compared with previous studies on the occurrence of L. passim from European honey bees from the same sampled States, infection rates of Africanized honey bees for L. passim were significantly higher in the State of Utah, but not for the other sampled States. This study provides evidence that feral honey bee populations do not necessarily have lower levels of honey bee parasites than managed honey bee colonies.

Effects of floral resources on honey bee populations in Mexico: Using dietary metabarcoding to examine landscape quality in agroecosystems.

The decline of honey bee populations significantly impacts the human food supply due to poor pollination and yield decreases of essential crop species. Given the reduction of pollinators, research into critical landscape components, such as floral resource availability and land use change, might provide valuable information about the nutritional status and health of honey bee colonies. To address this issue, we examine the effects of landscape factors like agricultural area, urban area, and climatic factors, including maximum temperature, minimum temperature, relative humidity, and precipitation, on honey bee hive populations and nutritional health of 326 honey bee colonies across varying landscapes in Mexico. DNA metabarcoding facilitated the precise identification of pollen from 267 plant species, encompassing 243 genera and 80 families, revealing a primary herb-based diet. Areas characterized by high landscape diversity exhibited greater pollen diversity within the colony. Conversely, colonies situated in regions with higher proportions of agricultural and urban landscapes demonstrated lower bee density. The maximum ambient temperature outside hives positively correlated with pollen diversity, aligning with a simultaneous decrease in bee density. Conversely, higher relative humidity positively influenced both the bee density of the colony and the diversity of foraged pollen. Our national-level study investigated pollen dietary availability and colony size in different habitat types, latitudes, climatic conditions, and varied levels and types of disturbances. This effort was taken to gain a better insight into the mechanisms driving declines in honey bee populations. This study illustrates the need for more biodiverse agricultural landscapes, the preservation of diverse habitats, and the conservation of natural and semi-natural spaces. These measures can help to improve the habitat quality of other bee species, as well as restore essential ecosystem processes, such as pollination and pest control.

Dominance of African racial ancestry in honey bee colonies of Mexico 30 years after the migration of hybrids from SouthAmerica.

The Africanized honey bee, a hybrid of Apis mellifera scutellata from Africa with European subspecies, has been considered an invasive species and a problem for beekeeping. Africanized bees arrived in Mexico in 1986, 30 years after their accidental release in Brazil. Although government programs were implemented for its eradication, Africanized populations persist in Mexico, but precise information on the patterns of genetic introgression and racial ancestry is scarce. We determined maternal and parental racial ancestry of managed and feral honey bees across the five beekeeping regions of Mexico, using mitochondrial (mtDNA, COI-COII intergenic region) and nuclear markers (94 ancestrally informative SNPs), to assess the relationship between beekeeping management, beekeeping region, altitude, and latitude with the distribution of maternal and parental racial ancestry. Results revealed a predominantly African ancestry in the Mexican honey bees, but the proportion varied according to management, beekeeping regions, and latitude. The Mexican honey bees showed 31 haplotypes of four evolutionary lineages (A, M, C, and O). Managed honey bees had mitochondrial and nuclear higher proportions of European ancestry than feral honey bees, which had a higher proportion of African ancestry. Beekeeping regions of lower latitudes had higher proportions of African nuclear ancestry. Managed and feral honey bees showed differences in the proportion of maternal and nuclear racial ancestry. Managed honey bees from the Yucatan Peninsula and feral honey bees had a higher mtDNA than nuclear proportions of African ancestry. Managed honey bees, except those on the Yucatan Peninsula, had a higher nuclear than mtDNA proportion of African ancestry. Our study demonstrates that Africanized honey bee populations are genetically diverse and well established in Mexico, which highlights the limitations of management and government programs to contain the Africanization process and demands the incorporation of this lineage in any breeding program for sustainable beekeeping.

Does roundup® affect worker bees (Apis mellifera) that inhabit areas of high agrochemical pressure?

Glyphosate-based herbicides (GBHs) find wide application in conventional agroecosystems due to their effective mode of action. The impact of herbicides on bees may be underestimated due to the scarcity of studies assessing various exposure routes to GBHs, including contact and ingestion of contaminated food. This study evaluated the survival, food consumption, and body weight of honey bee populations in three different locations, characterized by different degrees of exposure to GBHs. In bioassays, honey bees were exposed to diets containing sucrose solutions infused with glyphosate, with dosages ranging from 0 to 14 mg (a.i./bee). During the experiment, the honey bee population had a period of exposure (6 h) to the syrup infused with glyphosate. Mortality counts and feeder weight measurements were performed to assess the effects. A significant reduction in syrup intake was observed in all three bee populations during the Roundup® exposure phase, leading to a decrease in GBH intake. Notably, the decrease in syrup consumption emerged as the main factor contributing to the lower body weight observed among honey bees from low- and high-impact locations, persisting into the post-exposure period. Overall, the results demonstrate that honey bees in the high-impact region are more sensitive to Roundup®. However, studies using biochemical biomarkers are still necessary to unravel how glyphosate interferes with the acquisition and expenditure of energy during periods of exposure of honey bees and which physiological changes allow them to adapt to inhabited places with high agricultural pressure.

Core proteome mediated subtractive approach for the identification of potential therapeutic drug target against the honeybee pathogen Paenibacillus larvae.

American foulbrood (AFB), caused by the highly virulent, spore-forming bacterium Paenibacillus larvae, poses a significant threat to honey bee brood. The widespread use of antibiotics not only fails to effectively combat the disease but also raises concerns regarding honey safety. The current computational study was attempted to identify a novel therapeutic drug target against P. larvae, a causative agent of American foulbrood disease in honey bee. We investigated effective novel drug targets through a comprehensive in silico pan-proteome and hierarchal subtractive sequence analysis. In total, 14 strains of P.larvae genomes were used to identify core genes. Subsequently, the core proteome was systematically narrowed down to a single protein predicted as the potential drug target. Alphafold software was then employed to predict the 3D structure of the potential drug target. Structural docking was carried out between a library of phytochemicals derived from traditional Chinese flora (n>36,000) and the potential receptor using Autodock tool 1.5.6. Finally, molecular dynamics (MD) simulation study was conducted using GROMACS to assess the stability of the best-docked ligand. Proteome mining led to the identification of Ketoacyl-ACP synthase III as a highly promising therapeutic target, making it a prime candidate for inhibitor screening. The subsequent virtual screening and MD simulation analyses further affirmed the selection of ZINC95910054 as a potent inhibitor, with the lowest binding energy. This finding presents significant promise in the battle against P. larvae. Computer aided drug design provides a novel approach for managing American foulbrood in honey bee populations, potentially mitigating its detrimental effects on both bee colonies and the honey industry.

Using honey bee flight activity data and a deep learning model as a toxicovigilance tool

Automatic monitoring devices placed at the entrances of honey bee hives have facilitated the detection of various sublethal effects related to pesticide exposure, such as homing failure and reduced flight activity. These devices have further demonstrated that different neurotoxic pesticide molecules produce similar sublethal impacts on flight activity. The detection of these effects was conducted a posteriori, following the recording of flight activity data. This study introduces a method using an artificial intelligence model, specifically a recurrent neural network, to detect the sublethal effects of pesticides in real-time based on honey bee flight activity. This model was trained on a flight activity dataset comprising 42,092 flight records from 1107 control and 1689 pesticide-exposed bees. The model was able to classify honey bees as healthy or pesticide-exposed based on the number of flights and minutes spent foraging per day. The model was the least accurate (68.46%) when only five days of records per bee were used for training. However, the highest classification accuracy of 99%, a Cohen Kappa of 0.9766, a precision of 0.99, a recall of 0.99, and an F1-score of 0.99 was achieved with the model trained on 25 days of activity data, signifying near-perfect classification ability. These results underscore the highly predictive performance of AI models for toxicovigilance and highlight the potential of our approach for real-time and cost-effective monitoring of risks due to exposure to neurotoxic pesticide in honey bee populations.

Variability and Number of Circulating Complementary Sex Determiner (Csd) Alleles in a Breeding Population of Italian Honeybees under Controlled Mating.

In Apis mellifera, csd is the primary gene involved in sex determination: haploid hemizygous eggs develop as drones, while females develop from eggs heterozygous for the csd gene. If diploid eggs are homozygous for the csd gene, diploid drones will develop, but will be eaten by worker bees before they are born. Therefore, high csd allelic diversity is a priority for colony survival and breeding. This study aims to investigate the variability of the hypervariable region (HVR) of the csd gene in bees sampled in an apiary under a selection scheme. To this end, an existing dataset of 100 whole-genome sequences was analyzed with a validated pipeline based on de novo assembly of sequences within the HVR region. In total, 102 allelic sequences were reconstructed and translated into amino acid sequences. Among these, 47 different alleles were identified, 44 of which had previously been observed, while 3 are novel alleles. The results show a high variability in the csd region in this breeding population of honeybees.

Engineering Gut Symbionts: A Way to Promote Bee Growth?

Bees play a crucial role as pollinators, contributing significantly to ecosystems. However, the honeybee population faces challenges such as global warming, pesticide use, and pathogenic microorganisms. Promoting bee growth using several approaches is therefore crucial for maintaining their roles. To this end, the bacterial microbiota is well-known for its native role in supporting bee growth in several respects. Maximizing the capabilities of these microorganisms holds the theoretical potential to promote the growth of bees. Recent advancements have made it feasible to achieve this enhancement through the application of genetic engineering. In this review, we present the roles of gut symbionts in promoting bee growth and collectively summarize the engineering approaches that would be needed for future applications. Particularly, as the engineering of bee gut symbionts has not been advanced, the dominant gut symbiotic bacteria Snodgrassella alvi and Gilliamella apicola are the main focus of the paper, along with other dominant species. Moreover, we propose engineering strategies that will allow for the improvement in bee growth with listed gene targets for modification to further encourage the use of engineered gut symbionts to promote bee growth.

Understanding the Impact of Heat Stress on Honeybee Populations: Insights into Thermoregulation, Colony Dynamics, and Environmental Interactions

Nowadays, heat stress is emerging as a significant issue for honeybees in apiculture due to its potential to negatively impact the honey bees' health, the bee colony, and the economic stability. This review aims to thoroughly analyze the impact of heat stress on honeybee populations by consolidating existing research to provide accurate information. The thermoregulation process in honeybees and associated behavioral and molecular adaptations in worker bees, specific to Apis mellifera. Additionally covers the various ways that individual bees respond to heat stress, including changes in their metabolic rate and feeding habits. Furthermore, the paper provides a comprehensive analysis of how heat stress affects the entire bee colony, including detrimental effects on brood development, decreased productivity, and heightened susceptibility to illnesses and parasites. Also, it investigates the correlation between heat stress and other stressors, such as pesticide exposure, nutritional stress, biotic pressures, habitat loss, and the combined effects on bee health. To safeguard these important pollinators from the negative effects of climate change, this review stresses the need of interdisciplinary research and the need of identifying health stress as a major component influencing honeybee populations.

A colony health and economic comparison between mite resistant and commercial honey bees (Hymenoptera: Apidae).

Honey bees (Apis mellifera L.) are the premier agricultural pollinators with direct ecological value and are key to some agro-economies. Major factors have negatively impacted honey bee health in the past 2 decades with Varroa (Varroa destructor Anderson and Trueman) infestation rising as a principal predictor of colony mortality. A key strategy deployed in Varroa management is breeding for resistant honey bee populations that can maintain comparable levels of productivity as nonresistant populations. In this study, we examine one such population, Hilo honey bees, within the context of a common garden contrast with a commercial population in a stationary honey production operation. We compare colony survival, health, yield, and profit outcomes to show how this specific breeding population retains a profit value in honey production operations while maintaining higher survival and lower Varroa infestation levels than the commercial population. This information can be used by commercial beekeepers to make best management practice decisions and inspire further work examining what trade-offs, if any, are present in this Varroa-resistant population.

Impact of copper and zinc oral chronic exposure on Carniolan honey bee survival and feeding preference.

Honey bees are important plant pollinators and honey producers. Contamination of the environment with metals can lead to a decline in honey bee populations. Copper (Cu) and zinc (Zn) salts are commonly used as fungicides and foliar fertilizers. In this study, we investigated the effects of 10-day chronic oral exposure to different concentrations of Cu (CuSO4) and Zn (ZnCl2) on survival and feeding rates of Carniolan honey bees in laboratory conditions. We found that mortality in honey bee workers increased in a concentration-dependent manner and that Cu (lethal concentration [LC50] = 66 mg/l) was more toxic than Zn (LC50 = 144 mg/l). There was no difference in the feeding rate of Cu-treated bees for the different concentrations tested, but the feeding rate decreased with the increase in Zn concentration. To determine feeding preference or avoidance for Cu and Zn, we conducted 2-choice 24-h feeding experiments. We demonstrated that honey bees preferred Zn-containing solutions compared to the control diet. A two-choice experiment with Cu showed a tendency for honey bees to be deterred by Cu at high concentrations; however, it was not statistically significant. In summary, our results suggest that honey bee workers may suffer adverse effects when exposed to ecologically relevant concentrations of Cu and Zn.

High variation of worker cell and morphology between two adjacent populations of honey bee, Apis cerana (Hymenoptera, Apidae)

Honey bee population inhabiting among different geographic regions often exhibit distinctive traits and phenotypes as a means of enhancing their adaptation to local environmental conditions. Morphological difference of worker was used to reflect the honey bee population locality adaptation and as one of the important markers of species evolution. Here, four comb cell and seven morphology characters of honey bee Apis cerana from two adjacent populations of Yunnan Province were measured to explore the effect of local adaptation on worker comb cell and morphology. Results showed that the characters of worker comb cell and morphology was significant difference between samples from these two local populations of A. cerana. It was separated into two groups which corresponding into the general A. cerana geographic population of Yungui Plateau and South Yunnan base on worker comb cell and morphology character. The worker comb cell size and morphology of A. cerana from Qujing were found to be significantly larger than those from Cangyuan. The indices that showed the most significantly different between populations were cell depth and right forewing length. Moreover, a strong positive correlation was observed between the cell diagonal diameter and the right forewing length, with a correlation coefficient 0.575. In conclusion, honey bee A. cerana population appear high variation in comb cell and morphology to adapt the locality environment. The forewing length of worker was the most significant variation indices between geographic populations, and could be as an indicator of worker cell and morphology among different A. cerana geographic populations.

Genetic Profile of Greek Indigenous Honey Bee Populations, Local Extinctions, Geographical Distinction, and Patterns, by Using mtDNA COI and Nuclear CSD Gene Analysis Markers

Evaluation and conservation of local genetic resources of the domestic honey bee populations is important, especially in regions with high diversity levels as well as high honey bee colony density. Greece is rich in honey bee biodiversity, hosting several subspecies, with the status of them being, though, doubtful. The purpose of the present study was to investigate the genetic relationships of both stationary and movable honey bee populations, originating from many location throughout Greece. Two molecular markers were utilized, namely, the conserved mitochondrial COI gene and the highly variable complementary sex determination (CSD) gene. Samples were collected from nine distant populations: eight populations from colonies that followed the traditional stationary beekeeping model and one following the modern migratory beekeeping model type, where the hives are transferred from place to place according to the season. Regardless the beekeeping model, all populations were characterized by sufficient genetic diversity indicating no signs of inbreeding or any bottleneck effects. Nevertheless, genetic differentiation and phylogenetic analysis in comparison with haplotypes obtained from GenBank revealed a genetic admixture pattern suggesting that movement causes genetic homogeneity, occasionally in the stable reared populations as well. Interestingly, two populations, namely, Kastoria and Protokklisi, belonging to A. m. macedonica population, were significantly differentiated, supporting the maintenance of their genetic integrity. Unfortunately, on the other hand, genetic structure of the populations from Crete (Sasalos population) provided evidence that the indigenous breed from the island, A. m. adami, has probably gone extinct. Future management strategies should focus on the conservation of the local genetic resources in which distinct genetic identity has been sustained.

The Nutritional Year-Cycle of Italian Honey Bees (Apis mellifera ligustica) in a Southern Temperate Climate

Nutrition is a key aspect influencing honey bee health and overwintering. Since honey bee seasonality in southern temperate climates represents a significant research gap, this study conducted long-term monitoring of honey bees in the Mediterranean (Sassari, Italy). Specifically, individual weight, fat body, and size measurements (head, thorax, abdomen, and total body) were recorded monthly so to detect changes in the nutrient storage of worker bees during an annual cycle. Data were analysed according to sampling date, climate (temperature, precipitation, and daylength), and flower diversity and were conducted for nurse and forager bees separately. The nutritional honey bee year-cycle generally followed the nectar flow and showed two critical timepoints: summer and winter dearth. A short cessation of activities in late fall/early winter coupled with an increase in nutrient storage indicated the presence of winter bees. Precipitation was found to play an important role in honey bee nutrition in the study area through its impacts on colony demography and plants in particular illustrating how climate change could pose a threat to European honey bee populations in the future. These results provide valuable insights into the nutritional dynamics of Apis mellifera ligustica in the Mediterranean that could support management decisions to improve overwintering success and prevent unnecessary colony losses.

Antibiotic exposure alters the honeybee gut microbiota and may interfere with the honeybee behavioral caste transition.

Behavioral division is essential for the sustainability and reproduction of honeybee populations. While accumulating evidence has documented that antibiotic exposure interferes with bee behavioral divisions, how the gut microbiome, host physiology, and genetic regulation are implicated in this process remains understudied. Here, by constructing single-cohort colonies, we validated that the gut microbiota varied in composition between age-matched nurse and forager bees. Perturbing the gut microbiota with a low dose of antibiotic retained the gut bacterial size, but the structure of the microbial community continuously diverged from the control group after antibiotic treatment. Fewer foragers were observed in the antibiotic groups in the field experiment. A combinatorial effect of decreased gut metabolic gene repertoires, reduced brain neurotransmitter titers, and downregulated brain immune genes could potentially be related to behavioral tasks transition delay. This work indicates that the disturbance to both the gut microbiome and host physiologies after antibiotic exposure may have implications on social behavior development, highlighting the need for further research focusing on antibiotic pollution threatening the honeybee population's health.