Location: Carl Hayden Bee Research Center
2023 Annual Report
Objectives
Our long-term objective is to understand the structure and function of the honey bee microbiome in health and disease. Using a combination of laboratory and field approaches we will further our understanding of the diversity, abundance, persistence and functional capacities of the microorganisms that occur in the hive environment, the alimentary tracts of queens, workers and developing larvae. This information will be applied to the diagnosis and management of disease associated with commercial beekeeping. Industry applications include management strategies to reduce the severity of brood disease, diagnostic tools for queen health and productivity, and a novel context to assess disease prevention and progression.
The studies outlined in this Project Plan are directed at understanding the healthy microbial balance of a honey bee colony, with particular emphasis on dysbiotic states as precursors to disease. In a social insect like the honey bee, disease must be considered at many levels of organization (Evans and Spivak 2010). This rule also applies to beneficial host-microbe associations. We hypothesize that bacteria commonly shared among developmental stages, tissues, and reproductive castes may represent cryptic drivers of disease evolution (Figure 1). The long-term objective of this project is to identify native microbes that promote or discourage disease. Specifically, during the next five years we will focus on the following objectives.
Objective 1: Develop an integrated research approach (e.g. improved sampling and analytical methods) for the understanding and the management of honey bee larval microbiota, immune priming and brood disease. [NP305, Component 2, Problem Statements 2A and 2B] (Anderson)
Sub-objective 1A: Enumerate, identify, and characterize the microbial succession of healthy and diseased larvae. (Anderson)
Sub-objective 1B: Identify the species and interactions that cause or contribute to larval disease and/or affect larval immune response. (Anderson)
Objective 2: Analyze the population dynamics of the adult honey bee gut microbiota, and extended microbiota, with reference to species and strain variation, ecological niches, potential for functional redundancy, and corresponding host responses. [NP305, Component 2, Problem Statement 2B] (Anderson, Carroll)
Sub-objective 2A: Determine gut succession of the queen microbiota with respect to bacterial function, occupied niche, hive environment and host gene expression. (Anderson)
Sub-objective 2B: Determine how worker trophallactic feeding of queens is associated with the microbiota, queen quality, and worker-queen interactions in established queens. (Carroll, Anderson)
Objective 3: Investigate the effects of plant compounds on honey bee microbiota, their contributions to bee immunity, and their detoxification at the individual and colony-levels. [NP305, Component 2, Problem Statements 2A and 2B] (Anderson, Palmer-Young)
Sub-objective 3A: Determine the effect of plant secondary metabolites on microbial health of workers. (Palmer-Young, Anderson)
Sub-objective 3B: Determine the effect of recalcitrant polysaccharides on host-microbial function in workers. (Anderson)
Approach
Objective 1. Develop an integrated research approach (e.g. improved sampling and
analytical methods) for the understanding and the management of honey bee larval microbiota, immune priming and brood disease. [NP305, Component 2, Problem Statements 2A and 2B] (Anderson)
Sub-objective 1A: Enumerate, identify, and characterize the microbial succession of healthy and diseased larvae.
Hypothesis 1A: The microbial communities associated with phenotypically healthy and diseased larvae
do not differ.
Sub-objective 1B: Identify the species and interactions that cause or contribute to larval disease and/or affect larval immune response (Anderson)
Hypothesis 1B: Larval disease defined phenotypically as EFB or EFB-like is due solely to M. plutonius. Objective 2: Analyze the population dynamics of the adult honey bee gut microbiota, and extended microbiota, with reference to species and strain variation, ecological niches, potential for functional redundancy, and corresponding host responses. [NP305, Component 2, Problem Statement 2B] (Anderson, Carroll)
Sub-objective 2A: Determine gut succession of the queen microbiota with respect to bacterial function, occupied niche, hive environment and host gene expression. (Anderson)
Hypothesis 2A: Microbial succession of queen alimentary tracts and host gene expression does not differ by niche and early hive environment.
Sub-objective 2B: Determine how worker trophallactic feeding of queens is associated with the microbiota, queen quality, and worker-queen interactions in established queens. (Carroll, Anderson)
Hypothesis 2B: Selective trophallactic feeding of queens by workers is associated with the queen or worker microbiota, queen and worker quality, and worker-queen interactions mediated by pheromone exchanges.
Objective 3: Investigate the effects of plant compounds on honey bee microbiota, their contributions to bee immunity, and their detoxification at the individual and colony-levels. [NP305, Component 2, Problem Statements 2A and 2B] (Anderson, Palmer-Young)
Sub-objective 3A: Determine the effect of plant secondary metabolites on microbial health of workers. (Palmer-Young, Anderson)
Hypothesis 3A: Hindgut microbial communities and/or host health metrics are unaffected by plant secondary metabolites in the diet. Sub-objective 3B: Determine the effect of recalcitrant polysaccharides on host-microbial function in workers. (Anderson)
Hypothesis 3B: Hindgut microbial communities and/or host health metrics are unaffected by the addition of recalcitrant polysaccharides in the diet.
Progress Report
This report documents fiscal year (FY) 2023 progress for project 2022-21000-021-000D, "The Honey Bee Microbiome in Health and Disease".
In support of Objectives 1, 2, and 3, ARS researchers in Tucson, Arizona, performed a meta-analysis of 3500 publicly available Illumina libraries examining the hypothesis of a social network microbiota, and niche specificity of bacterial species in queen and worker guts. The ARS researchers selected studies to represent tissue-specific alimentary tract samples, both aerobic and anaerobic, and various aerobic colony niches including mouthparts, foreguts, social glands, developing larvae and stored nutrition. The research results indicate that aerobic gut and gland niches of queens and workers share their microbiome with developing larvae and nutritional resources defining the social network microbiota. Experimental factors tissue type, reproductive caste, and behavioral caste were all significant explanations for within and between sample diversity. The researchers confirmed that 10 genera were present at a minimum of 1% relative abundance shared by greater than 70% of all samples. The results detail niche specificity of bacterial species by tissue and niche, and by reproductive and behavioral caste. These results provide conclusive evidence for a social network (holobiont) microbiota fashioned by worker behavior and shared throughout aerobic resource space of the colony and built structure. In general, our results contribute novel insights into the total core microbiota, species specificity and niche fidelity. More specifically, our consolidation effort highlights undescribed bacteria that likely play major functional roles in the gut and colony, like the unnamed Bombella sp. prevalent and abundant in queen guts. Defining the social network microbiota, and gut microbiota at the level of species contributes to a systems-based understanding of opportunistic disease, social hygiene and gut microbiome resilience in the honey bee.
For Objective 1, ARS researchers intensified thier efforts to understand brood disease throughout the United States. Multi-state collaborations have been established with the Apiary Inspectors of America to record and verify various forms of brood disease, including detailed images and covariate colony metrics from both recovered and deceased hives. A large collection of images depicting various known types of brood disease has been curated, to train image recognition software to identify disease phenotypes with some level of certainty. ARS researchers are continually processing samples in the microbiology lab to validate the image tool, and characterize the virus, bacteria and fungi associated with various larval disease states.
Also supporting Objective 1, ARS researchers continued their efforts to understand various forms of brood disease focusing on the virulence factors of European foulbrood. They have obtained, characterized, and sequenced More than 300 isolates that tested positive for M. plutonius by PCR have been obtained, characterized, and sequenced. From these, Multi-locus sequence analyses were perfromed on the first set of 96 isolate samples collected across six different sites in Michigan in 2022. They found unique isolates belonging to nine sequence types, all of which were found to cluster in Clonal Complex CC3 and CC12 according to goeBURST analysis. Two of the new sequence types differed from all known types by a novel allele of the gbpB locus. The remaining three previously unreported sequence types were new MLST allelic combinations of known alleles. Multiple sequence types were found at four of the six Michigan sites where M. plutonius was identified. Two sites produced only a single sequence type. The other four sites contained four or five sequence types each. ST12 and ST19 were represented most often in these multiple-strain sites. Importantly, each site sampled a single colony, revealing that multiple strains may simultaneously contribute to EFB disease states. Further supporting this, more than one distinct sequence type within a single larva in eight cases was found. Seven of these cases included ST12 paired with one other sequence type. ARS researchers further screened all isolates for the melissotoxin A (mtxA) gene, which is carried on the plasmid pMP19 and may be an important virulence factor for European foulbrood disease. Thirty nine of the 96 isolates harbored this virulence gene. These findings are being compared to other geographic data from Europe.
Supporting Objective 2, ARS researchers investigated the gene expression of variably aged queens as part of a longitudinal study on commercial colony health. Queen failures consistently ranked with Varroa mites as the most prominent cause of yearly colony losses. Additionally, beekeepers prophylactically replace queens annually because younger queens are generally healthier and more productive despite the capacity for queen lifespan to exceed five years. ARS researchers in Tucson, Arizona, published two large studies exploring queen health with its relationship to the microbiome. The compilation of available data suggest that Alpha 2.1 decreases dramatically with age over the first year of life. Because this factor correlates with significantly decreased brood production, ARS researchers hypothesize that the decrease in Alpha 2.1 contributes to reduced queen fecundity. To examine differences in metabolic output, the researchers placed newly mated commercially produced queens in either small containment cages (i.e., queen bank) or free-running and laying eggs in colonies. Feeding intensity, social context, and metabolic demand differ greatly between the two environments. A microbiome analysis examining the queen’s mouthparts, midguts, ileums, and rectums, and associated gene expression analysis of other tissues found that both social context and queen breeder source affect gut microbiota and associated queen metabolism. In the ileum, upregulation of most immune and oxidative stress genes occurred regardless of treatment conditions, suggesting post-mating effects on gut gene expression. Counterintuitively, queens exposed to the more social colony environment contained significantly less bacterial diversity indicative of social immune factors shaping the queen’s microbiome. Queens housed in queen banks resembled much older queens with decreased beneficial bacteria in the hindgut, and significantly larger ileum microbiotas, dominated by blooms of worker-associated gut bacteria. Combined with earlier findings, it is evident that the queen gut microbiota experiences an extended period of microbial succession associated with queen breeder source, post-mating development and colony assimilation. The results suggest that queens may produce signals based on the microbiome that are perceived by workers. In collaboration with commercial beekeepers. ARS researchers plan to test these hypotheses in the coming year. To explore this relationship further, they have started a collaboration with the Daniel K. Inouye U.S. Pacific Basin Agricultural Research Center to pacbio sequence full length 16S reads and metatranscriptomes of variably aged queen hindguts.
Also, supporting Objective 2, a large scale longitudinal experiment was established in Illinois commercial colonies to examine the effect of queen age and the impact of microbiota on queen-worker interactions through overwintering and early spring almond pollination. Pollination colonies headed by either older queens or younger queens (requeened this spring) were initially sampled to examine the impact of queen age, with 40 queens terminally sampled at the first time point. Older queens apparently develop less efficient microbiota and experience lower queen productivity over time compared to younger queens. During mid-winter resumption of ovary activity, younger queens allocate proportionally more nutrients to ovaries than non-reproductive tissues compared to older queens. Queen-retinue worker interactions and colony performance were assessed to provide estimates of worker support of queens and colony productivity. Workers that fed the queen and workers that attempted to feed the queen (but were rejected) were sampled along with the queen for later assessments of how microbiota impact queen health, worker trophallactic feeding, and semiochemical signaling that governs food exchanges. Queens, workers, and colonies will be further sampled and analyzed at three time points through overwintering and almond pollination to determine impacts of microbiota and ovary activation on queen and colony productivity.
Supporting Objective 3, ARS researchers continued to examine the effects of plant products on the microbiome. In other host-microbial systems including humans, the overgrowth of yeast in the gut is problematic. The researchers tested the effect of plant resins applied throughout the colony as propolis by worker bees. They found that propolis enrichment radically restructures the bacterial-fungal relationship throughout the gut and hive. The fungi that populate these environments are still a functional mystery, but sugar tolerant yeasts seem to be most prevalent and abundant throughout the social resource niche.
More specifically, with propolis enrichment, diversity was significantly decreased, and the social network microbiota found on the mouthparts and throughout social resource space increased 10X comprised primarily of beneficial probiotic species Bombella apis, Apilactobacillus kunkeei, and Fructobacillus fructosus. The gut microbiota did not alter substantially in structure, but increased significantly in size, increasing by 3X, while the collective gut fungi (primarily yeasts) were reduced by 10X. Known to inhibit fungal growth in the colony and lab, propolis appears to have a therapeutic effect on virtually every niche in the colony enhancing the microbiota of the worker gut and social resource space.
Accomplishments
1. Artificial intelligence can diagnose brood disease. Honey bee brood disease causes significant colony loss in the United States, but diagnosis based on larval symptomology is subjective and often context dependent. Antibiotics are typically used prophylactically to treat bacterial diseases such as European Foulbrood, but this breeds molecular resistance, causes dysbiosis of the gut microbiome, and often fails to treat the underlying illness. To address this problem, ARS reseachers in Tucson, Arizona, are using machine learning to modernize brood disease diagnosis. Based on samples and corresponding images of diseased larvae collected from throughout the United States, ARS researchers have recovered a variety of known and unknown disease-associated bacteria and virus from samples diagnosed as known disease or idiopathic. Preliminary machine learning algorithms have been successful in predicting the microbiome result using only image symptomology. This resource allows diagnosis of early brood disease based on a smart phone photograph, and represents a valuable resource for beekeepers, apiary inspectors, and scientists.
2. Propolis is a potent prebiotic that restructures the fungal-bacterial relationship in the worker bee gut and colony. In other host-microbial systems including humans, the overgrowth of yeast in the gut is problematic. ARS researchers in Tucson, Arizona, tested the effect of plant resins on fungi applied throughout the colony as propolis by worker bees. The researchers found that propolis enrichment radically restructures the bacterial-fungal relationship throughout the gut and hive. Collective gut fungi, primarily yeasts, were reduced (10x), bacterial diversity decreased significantly, host immune gene expression was collectively reduced, and beneficial probiotic species increased dramatically in both the worker gut (3x) and throughout the hive environment (10x). The positive impact of propolis processing on immunity, disease and microbiota informs beekeepers concerning the economic viability associated with installing propolis traps within their hives.
3. Starvation-associated volatiles from adult honey bee workers serve as attractants to nest workers. Provided in critical times of forage dearth, the palatability and subsequent consumption of supplemental nutrition can vary greatly. Adult honey bees deprived of food resources solicit food donation from other workers, who in turn provide nutrients in the form of glandular secretions. ARS researchers in Tucson, Arizona, identified odors that attract workers (e.g. methyl benzoate) and mediate trophallactic exchanges among food donors and receivers within the nest. Identification of odorants mediating such trophallactic exchanges provides insight into feeding interactions of nest bees with other castes/life stages and provides a mechanism by which beekeeper-supplied supplemental nutrition could be made more palatable.
