Allele Frequencies of Genetic Variants Associated with Varroa Drone Brood Resistance (DBR) in Apis mellifera Subspecies across the European Continent.

Implementation of marker-assisted selection (MAS) in modern beekeeping would improve sustainability, especially in breeding programs aiming for resilience against the parasitic mite Varroa destructor. Selecting honey bee colonies for natural resistance traits, such as brood-intrinsic suppression of varroa mite reproduction, reduces the use of chemical acaricides while respecting local adaptation. In 2019, eight genomic variants associated with varroa non-reproduction in drone brood were discovered in a single colony from the Amsterdam Water Dune population in the Netherlands. Recently, a new study tested the applicability of these eight genetic variants for the same phenotype on a population-wide scale in Flanders, Belgium. As the properties of some variants varied between the two studies, one hypothesized that the difference in genetic ancestry of the sampled colonies may underly these contribution shifts. In order to frame this, we determined the allele frequencies of the eight genetic variants in more than 360 Apis mellifera colonies across the European continent and found that variant type allele frequencies of these variants are primarily related to the A. mellifera subspecies or phylogenetic honey bee lineage. Our results confirm that population-specific genetic markers should always be evaluated in a new population prior to using them in MAS programs.

Evaluation of Functional Properties of Some Lactic Acid Bacteria Strains for Probiotic Applications in Apiculture.

This study evaluates the suitability of three lactic acid bacteria (LAB) strains-Lactiplantibacillus plantarum, Lactobacillus acidophilus, and Apilactobacillus kunkeei-for use as probiotics in apiculture. Given the decline in bee populations due to pathogens and environmental stressors, sustainable alternatives to conventional treatments are necessary. This study aimed to assess the potential of these LAB strains in a probiotic formulation for bees through various in vitro tests, including co-culture interactions, biofilm formation, auto-aggregation, antioxidant activity, antimicrobial activity, antibiotic susceptibility, and resistance to high osmotic concentrations. This study aimed to assess both the individual effects of the strains and their combined effects, referred to as the LAB mix. Results indicated no mutual antagonistic activity among the LAB strains, demonstrating their compatibility with multi-strain probiotic formulations. The LAB strains showed significant survival rates under high osmotic stress and simulated gastrointestinal conditions. The LAB mix displayed enhanced biofilm formation, antioxidant activity, and antimicrobial efficacy against different bacterial strains. These findings suggest that a probiotic formulation containing these LAB strains could be used for a probiotic formulation, offering a promising approach to mitigating the negative effects of pathogens. Future research should focus on in vivo studies to validate the efficacy of these probiotic bacteria in improving bee health.

Bridging the Gap between Field Experiments and Machine Learning: The EC H2020 B-GOOD Project as a Case Study towards Automated Predictive Health Monitoring of Honey Bee Colonies.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies' exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony's health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project's data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping.

Sericultural By-Products: The Potential for Alternative Therapy in Cancer Drug Design.

Major progress has been made in cancer research; however, cancer remains one of the most important health-related burdens. Sericulture importance is no longer limited to the textile industry, but its by-products, such as silk fibroin or mulberry, exhibit great impact in the cancer research area. Fibroin, the pivotal compound that is found in silk, owns superior biocompatibility and biodegradability, representing one of the most important biomaterials. Numerous studies have reported its successful use as a drug delivery system, and it is currently used to develop three-dimensional tumor models that lead to a better understanding of cancer biology and play a great role in the development of novel antitumoral strategies. Moreover, sericin's cytotoxic effect on various tumoral cell lines has been reported, but also, it has been used as a nanocarrier for target therapeutic agents. On the other hand, mulberry compounds include various bioactive elements that are well known for their antitumoral activities, such as polyphenols or anthocyanins. In this review, the latest progress of using sericultural by-products in cancer therapy is discussed by highlighting their notable impact in developing novel effective drug strategies.

Virus Prevalence in Egg Samples Collected from Naturally Selected and Traditionally Managed Honey Bee Colonies across Europe.

Monitoring virus infections can be an important selection tool in honey bee breeding. A recent study pointed towards an association between the virus-free status of eggs and an increased virus resistance to deformed wing virus (DWV) at the colony level. In this study, eggs from both naturally surviving and traditionally managed colonies from across Europe were screened for the prevalence of different viruses. Screenings were performed using the phenotyping protocol of the 'suppressed in ovo virus infection' trait but with qPCR instead of end-point PCR and a primer set that covers all DWV genotypes. Of the 213 screened samples, 109 were infected with DWV, 54 were infected with black queen cell virus (BQCV), 3 were infected with the sacbrood virus, and 2 were infected with the acute bee paralyses virus. It was demonstrated that incidences of the vertical transmission of DWV were more frequent in naturally surviving than in traditionally managed colonies, although the virus loads in the eggs remained the same. When comparing virus infections with queen age, older queens showed significantly lower infection loads of DWV in both traditionally managed and naturally surviving colonies, as well as reduced DWV infection frequencies in traditionally managed colonies. We determined that the detection frequencies of DWV and BQCV in honey bee eggs were lower in samples obtained in the spring than in those collected in the summer, indicating that vertical transmission may be lower in spring. Together, these patterns in vertical transmission show that honey bee queens have the potential to reduce the degree of vertical transmission over time.

Juvenile hormone pathway in honey bee larvae: A source of possible signal molecules for the reproductive behavior of Varroa destructor.

The parasitic mite Varroa destructor devastates honey bee (Apis mellifera) colonies around the world. Entering a brood cell shortly before capping, the Varroa mother feeds on the honey bee larvae. The hormones 20-hydroxyecdysone (20E) and juvenile hormone (JH), acquired from the host, have been considered to play a key role in initiating Varroa's reproductive cycle. This study focuses on differential expression of the genes involved in the biosynthesis of JH and ecdysone at six time points during the first 30 hr after cell capping in both drone and worker larvae of A. mellifera. This time frame, covering the conclusion of the honey bee brood cell invasion and the start of Varroa's ovogenesis, is critical to the successful initiation of a reproductive cycle. Our findings support a later activation of the ecdysteroid cascade in honey bee drones compared to worker larvae, which could account for the increased egg production of Varroa in A. mellifera drone cells. The JH pathway was generally downregulated confirming its activity is antagonistic to the ecdysteroid pathway during the larva development. Nevertheless, the genes involved in JH synthesis revealed an increased expression in drones. The upregulation of jhamt gene involved in methyl farnesoate (MF) synthesis came into attention since the MF is not only a precursor of JH but it is also an insect pheromone in its own right as well as JH-like hormone in Acari. This could indicate a possible kairomone effect of MF for attracting the mites into the drone brood cells, along with its potential involvement in ovogenesis after the cell capping, stimulating Varroa's initiation of egg laying.

Advances in Editing Silkworms (Bombyx mori) Genome by Using the CRISPR-Cas System.

CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated) represents a powerful genome editing technology that revolutionized in a short period of time numerous natural sciences branches. Therefore, extraordinary progress was made in various fields, such as entomology or biotechnology. Bombyx mori is one of the most important insects, not only for the sericulture industry, but for numerous scientific areas. The silkworms play a key role as a model organism, but also as a bioreactor for the recombinant protein production. Nowadays, the CRISPR-Cas genome editing system is frequently used in order to perform gene analyses, to increase the resistance against certain pathogens or as an imaging tool in B. mori. Here, we provide an overview of various studies that made use of CRISPR-Cas for B. mori genome editing, with a focus on emphasizing the high applicability of this system in entomology and biological sciences.

A gene for resistance to the Varroa mite (Acari) in honey bee (Apis mellifera) pupae.

Social insect colonies possess a range of defences which protect them against highly virulent parasites and colony collapse. The host-parasite interaction between honey bees (Apis mellifera) and the mite Varroa destructor is unusual, as honey bee colonies are relatively poorly defended against this parasite. The interaction has existed since the mid-20th Century, when Varroa switched host to parasitize A. mellifera. The combination of a virulent parasite and relatively naïve host means that, without acaricides, honey bee colonies typically die within 3 years of Varroa infestation. A consequence of acaricide use has been a reduced selective pressure for the evolution of Varroa resistance in honey bee colonies. However, in the past 20 years, several natural-selection-based breeding programmes have resulted in the evolution of Varroa-resistant populations. In these populations, the inhibition of Varroa's reproduction is a common trait. Using a high-density genome-wide association analysis in a Varroa-resistant honey bee population, we identify an ecdysone-induced gene significantly linked to resistance. Ecdysone both initiates metamorphosis in insects and reproduction in Varroa. Previously, using a less dense genetic map and a quantitative trait loci analysis, we have identified Ecdysone-related genes at resistance loci in an independently evolved resistant population. Varroa cannot biosynthesize ecdysone but can acquire it from its diet. Using qPCR, we are able to link the expression of ecdysone-linked resistance genes to Varroa's meals and reproduction. If Varroa co-opts pupal compounds to initiate and time its own reproduction, mutations in the host's ecdysone pathway may represent a key selection tool for honey bee resistance and breeding.