Clustering, persistence and control of a pollinator brood disease: epidemiology of American foulbrood

Proteomic insight into the interaction of Paenibacillus larvae with honey bee larvae before capping collected from an American foulbrood outbreak: Pathogen proteins within the host, lysis signatures and interaction markers

American foulbrood (AFB) is a devastating disease of honey bees. There remains a gap in the understanding of the interactions between the causative agent and host, so we used shotgun proteomics to gain new insights. Nano-LC-MS/MS analysis preceded visual description and Paenibacillus larvae identification in the same individual sample. A further critical part of our methodology was that larvae before capping were used as the model stage. The identification of the virulence factors SplA, PlCBP49, enolase, and DnaK in all P. larvae-positive samples was consistent with previous studies. Furthermore, the results were consistent with the array of virulence factors identified in an in vitro study of P. larvae exoprotein fractions. Although an S-layer protein and a putative bacteriocin were highlighted as important, the microbial collagenase ColA and InhA were not found in our samples. The most important virulence factor identified was isoform of neutral metalloproteinase (UniProt: V9WB82), a major protein marker responsible for the shift in the PCA biplot. This protein is associated with larval decay and together with other virulence factors (bacteriocin) can play a key role in protection against secondary invaders. Overall, this study provides new knowledge on host-pathogen interactions and a new methodical approach to study the disease.

Establishment of apiary-level risk of American foulbrood through the detection of Paenibacillus larvae spores in pooled, extracted honey in Saskatchewan

Paenibacillus larvae, the causative agent of American foulbrood (AFB), produces spores that may be detectable within honey. We analyzed the spore content of pooled, extracted honey from 52 large-scale (L) and 64 small-scale (S) Saskatchewan beekeepers over a two-year period (2019-2020). Our objectives were: (i) establish reliable prognostic reference ranges for spore concentrations in extracted honey to determine future AFB risk at the apiary level; (ii) identify management practices as targets for mitigation of risk. P. larvae spores were detected in 753 of 1476 samples (51%). Beekeepers were stratified into low (< 2 spores/gram), moderate (2- < 100 spores/gram), and high (≥ 100 spores/gram) risk categories. Of forty-nine L beekeepers sampled in 2019, those that reported AFB in 2020 included 0/26 low, 3/18 moderate, and 3/5 high risk. Of twenty-seven L beekeepers sampled in 2020, those that reported AFB in 2021 included 0/11 low, 2/14 moderate, and 1/2 high risk. Predictive modelling included indoor overwintering of hives, purchase of used equipment, movement of honey-producing colonies between apiaries, beekeeper demographic, and antimicrobial use as risk category predictors. Saskatchewan beekeepers with fewer than 2 spores/gram in extracted honey that avoid high risk activities may be considered at low risk of AFB the following year.

Identifying the climatic drivers of honey bee disease in England and Wales

Honey bee colony health has received considerable attention in recent years, with many studies highlighting multifactorial issues contributing to colony losses. Disease and weather are consistently highlighted as primary drivers of colony loss, yet little is understood about how they interact. Here, we combined disease records from government honey bee health inspections with meteorological data from the CEDA to identify how weather impacts EFB, AFB, CBP, varroosis, chalkbrood and sacbrood. Using R-INLA, we determined how different meteorological variables influenced disease prevalence and disease risk. Temperature caused an increase in the risk of both varroosis and sacbrood, but overall, the weather had a varying effect on the six honey bee diseases. The risk of disease was also spatially varied and was impacted by the meteorological variables. These results are an important step in identifying the impacts of climate change on honey bees and honey bee diseases.

Microbiota dysbiosis in honeybee (Apis mellifera L.) larvae infected with brood diseases and foraging bees exposed to agrochemicals

American foulbrood (AFB) disease and chalkbrood disease (CBD) are important bacterial and fungal diseases, respectively, that affect honeybee broods. Exposure to agrochemicals is an abiotic stressor that potentially weakens honeybee colonies. Gut microflora alterations in adult honeybees associated with these biotic and abiotic factors have been investigated. However, microbial compositions in AFB- and CBD-infected larvae and the profile of whole-body microbiota in foraging bees exposed to agrochemicals have not been fully studied. In this study, bacterial and fungal communities in healthy and diseased (AFB/CBD) honeybee larvae were characterized by amplicon sequencing of bacterial 16S rRNA gene and fungal internal transcribed spacer1 region, respectively. The bacterial and fungal communities in disordered foraging bees poisoned by agrochemicals were analysed. Our results revealed that healthy larvae were significantly enriched in bacterial genera Lactobacillus and Stenotrophomonas and the fungal genera Alternaria and Aspergillus. The enrichment of these microorganisms, which had antagonistic activities against the etiologic agents for AFB and CBD, respectively, may protect larvae from potential infection. In disordered foraging bees, the relative abundance of bacterial genus Gilliamella and fungal species Cystofilobasidium macerans were significantly reduced, which may compromise hosts' capacities in nutrient absorption and immune defence against pathogens. Significantly higher frequency of environmentally derived fungi was observed in disordered foraging bees, which reflected the perturbed microbiota communities of hosts. Results from PICRUSt and FUNGuild analyses revealed significant differences in gene clusters of bacterial communities and fungal function profiles. Overall, results of this study provide references for the composition and function of microbial communities in AFB- and CBD-infected honeybee larvae and foraging bees exposed to agrochemicals.

American foulbrood in a honeybee colony: spore-symptom relationship and feedbacks

BACKGROUND

The most severe bacterial disease of honeybees is American foulbrood (AFB). The epidemiology of AFB is driven by the extreme spore resilience, the difficulty of bees to remove these spores, and the considerable incidence of undetected spore-producing colonies. The honeybee collective defence mechanisms and their feedback on colony development, which involves a division of labour at multiple levels of colony organization, are difficult to model. To better predict disease outbreaks we need to understand the feedback between colony development and disease progression within the colony. We therefore developed Bayesian models with data from forty AFB-diseased colonies monitored over an entire foraging season to (i) investigate the relationship between spore production and symptoms, (ii) disentangle the feedback loops between AFB epidemiology and natural colony development, and (iii) discuss whether larger insect societies promote or limit within-colony disease transmission.

RESULTS

Rather than identifying a fixed spore count threshold for clinical symptoms, we estimated the probabilities around the relationship between spore counts and symptoms, taking into account modulators such as brood amount/number of bees and time post infection. We identified a decrease over time in the bees-to-brood ratio related to disease development, which should ultimately induce colony collapse. Lastly, two contrasting theories predict that larger colonies could promote either higher (classical epidemiological SIR-model) or lower (increasing spatial nest segregation and more effective pathogen removal) disease prevalence.

CONCLUSIONS

AFB followed the predictions of the SIR-model, partly because disease prevalence and brood removal are decoupled, with worker bees acting more as disease vectors, infecting new brood, than as agents of social immunity, by removing infected brood. We therefore established a direct link between disease prevalence and social group size for a eusocial insect. We furthermore provide a probabilistic description of the relationship between AFB spore counts and symptoms, and how disease development and colony strength over a season modulate this relationship. These results help to better understand disease development within honeybee colonies, provide important estimates for further epidemiological modelling, and gained important insights into the optimal sampling strategy for practical beekeeping and honeybee research.

Honeybee-Specific Lactic Acid Bacterium Supplements Have No Effect on American Foulbrood-Infected Honeybee Colonies

Paenibacillus larvae, the causative agent of American foulbrood (AFB), is the primary bacterial pathogen affecting honeybees and beekeeping. The main methods for controlling AFB are incineration of diseased colonies or prophylactic antibiotic treatment (e.g., with tylosin), neither of which is fully satisfactory. The search for superior means for controlling AFB has led to an increased interest in the natural relationships between the honeybee-pathogenic and mutualistic microorganisms and, in particular, the antagonistic effects of honeybee-specific lactic acid bacteria (hbs-LAB) against P. larvae These effects have been demonstrated only on individual larvae in controlled laboratory bioassays. Here we investigated whether supplemental administration of hbs-LAB had a similar beneficial effect on P. larvae infection at colony level. We compared experimentally AFB-infected colonies treated with hbs-LAB supplements to untreated and tylosin-treated colonies and recorded AFB symptoms, bacterial spore levels, and two measures of colony health. To account for the complexity of a bee colony, we focused on (Bayesian) probabilities and magnitudes of effect sizes. Tylosin reduced AFB disease symptoms but also had a negative effect on colony strength. The tylosin treatment did not, however, affect P. larvae spore levels and might therefore "mask" the potential for disease. hbs-LAB tended to reduce brood size in the short term but was unlikely to affect AFB symptoms or spores. These results do not contradict demonstrated antagonistic effects of hbs-LAB against P. larvae at the individual bee level but rather suggest that supplementary administration of hbs-LAB may not be the most effective way to harness these beneficial effects at the colony level.IMPORTANCE The previously demonstrated antagonistic effects of honeybee-derived bacterial microbiota on the infectivity and pathogenicity of P. larvae in laboratory bioassays have identified a possible new approach to AFB control. However, honeybee colonies are complex superorganisms where social immune defenses play a major role in resistance against disease at the colony level. Few studies have investigated the effect of beneficial microorganisms on bee diseases at the colony level. Effects observed at the individual bee level do not necessarily translate into similar effects at the colony level. This study partially fills this gap by showing that, unlike at the individual level, hbs-LAB supplements did not affect AFB symptoms at the colony level. The inference is that the mechanisms regulating the honeybee microbial dynamics within a colony are too strong to manipulate positively through supplemental feeding of live hbs-LAB and that new potential remedies identified through laboratory research have to be tested thoroughly in situ, in colonies.

An integrated management strategy to prevent outbreaks and eliminate infection pressure of American foulbrood disease in a commercial beekeeping operation

The bacterial disease American Foulbrood (AFB), caused by the Gram-positive bacterium Paenibacillus larvae, is considered the most contagious and destructive infectious disease affecting honeybees world-wide. The resilient nature of P. larvae bacterial spores presents a difficult problem for the control of AFB. Burning clinically symptomatic colonies is widely considered the only workable strategy to prevent further spread of the disease. Antibiotic use is banned in EU countries, and although used commonly in the U.S. and Canada, it only masks symptoms and does not prevent the further spread of the disease. Not surprisingly, there is an increased demand for chemical-free strategies to prevent and control of AFB. The aim of this study was to implement a management program with a long-term perspective to reduce infection pressure and eliminate AFB outbreaks. The study was conducted within a commercial beekeeping operation in central Sweden that has previously experienced reoccurring AFB outbreaks. For 5 years, P. larvae were cultured from adult bee samples taken in the fall. The following spring, any identified sub-clinically infected colonies were shaken onto new material and quarantined from the rest of the beekeeping operation. After the first year clinical symptoms were not again observed, and during the 5 years of the study the proportion of apiaries harbouring P. larvae spores decreased from 74% to 4%. A multinomial regression analysis also clearly demonstrated that the proportion of infected colonies with the highest levels of spore counts disproportionately declined so that by the end of the study the only remaining infected apiaries were in the lowest spore count category (the three higher spore count categories having been eradicated). These results demonstrate the importance of management practices on AFB disease epidemiology. Early detection of subclinical spore prevelance and quarantine management as presented here can provide an effective sustainable chemical-free preventive solution to reduce both the incidence of AFB outbreaks and continued transmission risk at a large-scale.

High-resolution maps of Swiss apiaries and their applicability to study spatial distribution of bacterial honey bee brood diseases

Honey bees directly affect and are influenced by their local environment, in terms of food sources, pollinator densities, pathogen and toxin exposure and climate. Currently, there is a lack of studies analyzing these data with Geographic Information Systems (GIS) to investigate spatial relationships with the environment. Particularly for inter-colonial pathogen transmission, it is known that the likelihood of a healthy colony to become infested (e.g., Varroosis) or infected (e.g., American foulbrood-AFB, European foulbrood-EFB) increases with higher colony density. Whether these transmission paths can actually be asserted at apiary level is largely unknown. Here, we unraveled spatial distribution and high-resolution density of apiaries and bacterial honey bee brood diseases in Switzerland based on available GIS data. Switzerland as 'model country' offers the unique opportunity to get apiary data since 2010 owing to compulsory registration for every beekeeper. Further, both destructive bee brood diseases (AFB and EFB) are legally notifiable in Switzerland, and EFB has an epizootic character for the last decades. As governmental data sets have to be ameliorated, raw data from the cantonal agricultural or veterinary offices have been included. We found a mean density of 0.56 apiaries per km2, and high resolution spatial analyzes showed strong correlation between density of apiaries and human population density as well as agricultural landscape type. Concerning two bacterial bee brood diseases (AFB, EFB), no significant correlation was detectable with density of apiaries on cantonal level, though a high correlation of EFB cases and apiary density became obvious on higher resolution (district level). Hence, Swiss EFB epizootics seem to have benefited from high apiary densities, promoting the transmission of pathogens by adult bees. The GIS-based method presented here, might also be useful for other bee diseases, anthropogenic or environmental factors affecting bee colonies.

Honeybee (Apis mellifera)-associated bacterial community affected by American foulbrood: detection of Paenibacillus larvae via microbiome analysis

Honeybee (Apis mellifera L.) workers act as passive vectors of Paenibacillus larvae spores, which cause the quarantine disease American foulbrood (AFB). We assessed the relative proportions of P. larvae within the honeybee microbiome using metabarcoding analysis of the 16 S rRNA gene. The microbiome was analyzed in workers outside of the AFB zone (control - AFB0), in workers from asymptomatic colonies in an AFB apiary (AFB1), and in workers from colonies exhibiting clinical AFB symptoms (AFB2). The microbiome was processed for the entire community and for a cut-off microbiome comprising pathogenic/environmental bacteria following the removal of core bacterial sequences; varroosis levels were considered in the statistical analysis. No correlation was observed between AFB status and varroosis level, but AFB influenced the worker bee bacterial community, primarily the pathogenic/environmental bacteria. There was no significant difference in the relative abundance of P. larvae between the AFB1 and AFB0 colonies, but we did observe a 9-fold increase in P. larvae abundance in AFB2 relative to the abundance in AFB1. The relative sequence numbers of Citrobacter freundii and Hafnia alvei were higher in AFB2 and AFB1 than in AFB0, whereas Enterococcus faecalis, Klebsiella oxytoca, Spiroplasma melliferum and Morganella morganii were more abundant in AFB0 and AFB1 than in AFB2.

A pan-European epidemiological study reveals honey bee colony survival depends on beekeeper education and disease control

Reports of honey bee population decline has spurred many national efforts to understand the extent of the problem and to identify causative or associated factors. However, our collective understanding of the factors has been hampered by a lack of joined up trans-national effort. Moreover, the impacts of beekeeper knowledge and beekeeping management practices have often been overlooked, despite honey bees being a managed pollinator. Here, we established a standardised active monitoring network for 5 798 apiaries over two consecutive years to quantify honey bee colony mortality across 17 European countries. Our data demonstrate that overwinter losses ranged between 2% and 32%, and that high summer losses were likely to follow high winter losses. Multivariate Poisson regression models revealed that hobbyist beekeepers with small apiaries and little experience in beekeeping had double the winter mortality rate when compared to professional beekeepers. Furthermore, honey bees kept by professional beekeepers never showed signs of disease, unlike apiaries from hobbyist beekeepers that had symptoms of bacterial infection and heavy Varroa infestation. Our data highlight beekeeper background and apicultural practices as major drivers of honey bee colony losses. The benefits of conducting trans-national monitoring schemes and improving beekeeper training are discussed.

Testing for clustering at many ranges inflates family-wise error rate (FWE)

BACKGROUND

Testing for clustering at multiple ranges within a single dataset is a common practice in spatial epidemiology. It is not documented whether this approach has an impact on the type 1 error rate.

METHODS

We estimated the family-wise error rate (FWE) for the difference in Ripley's K functions test, when testing at an increasing number of ranges at an alpha-level of 0.05. Case and control locations were generated from a Cox process on a square area the size of the continental US (≈3,000,000 mi2). Two thousand Monte Carlo replicates were used to estimate the FWE with 95% confidence intervals when testing for clustering at one range, as well as 10, 50, and 100 equidistant ranges.

RESULTS

The estimated FWE and 95% confidence intervals when testing 10, 50, and 100 ranges were 0.22 (0.20 - 0.24), 0.34 (0.31 - 0.36), and 0.36 (0.34 - 0.38), respectively.

CONCLUSIONS

Testing for clustering at multiple ranges within a single dataset inflated the FWE above the nominal level of 0.05. Investigators should construct simultaneous critical envelopes (available in spatstat package in R), or use a test statistic that integrates the test statistics from each range, as suggested by the creators of the difference in Ripley's K functions test.