A next generation sequencing approach for targeted Varroa destructor (Acari: Varroidae) mitochondrial DNA analysis based on honey derived environmental DNA

Environmental DNA methods for biosecurity and invasion biology in terrestrial ecosystems: Progress, pitfalls, and prospects

Analysis of environmental DNA (eDNA) enables indirect detection of species without the need to directly observe and sample them. For biosecurity and invasion biology, eDNA-based methods are useful to address biological invasions at all phases, from detecting arrivals to confirming eradication of past invasions. We conducted a systematic review of the literature and found that in biosecurity and invasion biology, eDNA has primarily been used to detect new incursions and monitor spread in marine and freshwater ecosystems, with much slower uptake in terrestrial ecosystems, reflecting a broader trend common to the usage of eDNA tools. In terrestrial ecosystems, eDNA research has mostly focussed on the use of eDNA metabarcoding to characterise biodiversity, rather than targeting biosecurity threats or non-native populations. We discuss how eDNA-based methods are being applied to terrestrial ecosystems for biosecurity and managing non-native populations at each phase of the invasion continuum: transport, introduction, establishment, and spread; across different management options: containment, control, and eradication; and for detecting the impact of non-native organisms. Finally, we address some of the current technical issues and caveats of eDNA-based methods, particularly for terrestrial ecosystems, and how these might be solved. As eDNA-based methods improve, they will play an increasingly important role in the early detection and adaptive management of biological invasions, and the implementation of effective biosecurity controls.

Environmental DNA/RNA for pathogen and parasite detection, surveillance, and ecology

Detection of pathogens, parasites, and other symbionts in environmental samples via eDNA/eRNA (collectively eNA) is an increasingly important source of information about their occurrence and activity. There is great potential for using such detections as a proxy for infection of host organisms in connected habitats, for pathogen monitoring and surveillance, and for early warning systems for disease. However, many factors require consideration, and appropriate methods developed and verified, in order that eNA detections can be reliably interpreted and adopted for surveillance and assessment of disease risk, and potentially inclusion in international standards, such as the World Organisation for Animal Health guidelines. Disease manifestation results from host-symbiont-environment interactions between hosts, demanding a multifactorial approach to interpretation of eNA signals.

Towards DNA-Based Methods Analysis for Honey: An Update

Honey is a natural product widely consumed all over the world due to its relationship with healthy benefits. Additionally, environmental and ethical issues have a higher weight in the consumer's choice to buy honey as a natural product. Following the high demand of this product, several approaches have been suggested and developed aiming at the assessment of honey's quality and authenticity. Target approaches, such as pollen analysis, phenolic compounds, sugars, volatile compounds, organic acids, proteins, amino acids, minerals, and trace elements, showed an efficacy, particularly concerning the honey origin. However, a special highlight is given to DNA markers, due to their useful applicability in environmental and biodiversity studies, besides the geographical, botanical, and entomological origins. Different DNA target genes were already explored for addressing diverse sources of honey DNA, with DNA metabarcoding attaining a relevant importance. This review aims to describe the latest advances on DNA-based methods applied in honey related studies, identifying the research needs for the development of new and additional required methodologies, and to select the most adequate tools for future research projects.

Metabarcoding of eDNA for tracking the floral and geographical origins of bee honey

Authentic honey products have a high commercial value and are often falsified via adulteration. Metabarcoding of environmental DNA (eDNA) from bacterial, floral, and entomological sources has recently been proposed as a useful tool for identifying and authenticating floral and geographical origins of bee honey. In this study, eDNA metabarcoding was applied to reveal the bacterial, plant, and honey bee DNA signatures of 48 commercial honey products from six different geographical origins. Bacterial DNA composition in commercial honey showed different relative abundance of Paenibacillus and Bacillus in geographically different samples, and high abundance of Methylobacterium in chestnut honey implying potential use of bacterial DNA composition for honey authentication. Using the chloroplast trnL (UAA) as a DNA marker, floral origins of commercial honey were investigated. Based on floral DNA signatures, 12 monofloral honey samples were identified among the 45 samples tested. Targeted amplicon sequencing of cytochrome oxidase I (COI) gene from entomological DNA identified three different Apis mellifera sequence variants, specific to geographic origin of honey, suggesting that COI can be implemented as a DNA marker to trace the origin of honey. Therefore, the current study demonstrated the potential of eDNA based metabarcoding as a robust tool for evaluating commercial bee honey by exploring their floral and geographical origins.

Applications of environmental DNA (eDNA) in agricultural systems: Current uses, limitations and future prospects

Global food production, food supply chains and food security are increasingly stressed by human population growth and loss of arable land, becoming more vulnerable to anthropogenic and environmental perturbations. Numerous mutualistic and antagonistic species are interconnected with the cultivation of crops and livestock and these can be challenging to identify on the large scales of food production systems. Accurate identifications to capture this diversity and rapid scalable monitoring are necessary to identify emerging threats (i.e. pests and pathogens), inform on ecosystem health (i.e. soil and pollinator diversity), and provide evidence for new management practices (i.e. fertiliser and pesticide applications). Increasingly, environmental DNA (eDNA) is providing rapid and accurate classifications for specific organisms and entire species assemblages in substrates ranging from soil to air. Here, we aim to discuss how eDNA is being used for monitoring of agricultural ecosystems, what current limitations exist, and how these could be managed to expand applications into the future. In a systematic review we identify that eDNA-based monitoring in food production systems accounts for only 4 % of all eDNA studies. We found that the majority of these eDNA studies target soil and plant substrates (60 %), predominantly to identify microbes and insects (60 %) and are biased towards Europe (42 %). While eDNA-based monitoring studies are uncommon in many of the world's food production systems, the trend is most pronounced in emerging economies often where food security is most at risk. We suggest that the biggest limitations to eDNA for agriculture are false negatives resulting from DNA degradation and assay biases, as well as incomplete databases and the interpretation of abundance data. These require in silico, in vitro, and in vivo approaches to carefully design, test and apply eDNA monitoring for reliable and accurate taxonomic identifications. We explore future opportunities for eDNA research which could further develop this useful tool for food production system monitoring in both emerging and developed economies, hopefully improving monitoring, and ultimately food security.

Molecular Detection and Differentiation of Arthropod, Fungal, Protozoan, Bacterial and Viral Pathogens of Honeybees

The honeybee Apis mellifera is highly appreciated worldwide because of its products, but also as it is a pollinator of crops and wild plants. The beehive is vulnerable to infections due to arthropods, fungi, protozoa, bacteria and/or viruses that manage to by-pass the individual and social immune mechanisms of bees. Due to the close proximity of bees in the beehive and their foraging habits, infections easily spread within and between beehives. Moreover, international trade of bees has caused the global spread of infections, several of which result in significant losses for apiculture. Only in a few cases can infections be diagnosed with the naked eye, by direct observation of the pathogen in the case of some arthropods, or by pathogen-associated distinctive traits. Development of molecular methods based on the amplification and analysis of one or more genes or genomic segments has brought significant progress to the study of bee pathogens, allowing for: (i) the precise and sensitive identification of the infectious agent; (ii) the analysis of co-infections; (iii) the description of novel species; (iv) associations between geno- and pheno-types and (v) population structure studies. Sequencing of bee pathogen genomes has allowed for the identification of new molecular targets and the development of specific genotypification strategies.

Honey Environmental DNA Can Be Used to Detect and Monitor Honey Bee Pests: Development of Methods Useful to Identify Aethina tumida and Galleria mellonella Infestations

Environmental DNA (eDNA) contained in honey derives from the organisms that directly and indirectly have been involved in the production process of this matrix and that have played a role in the hive ecosystems where the honey has been produced. In this study we set up PCR-based assays to detect the presence of DNA traces left in the honey by two damaging honey bee pests: the small hive beetle (Aethina tumida) and the greater wax moth (Galleria mellonella). DNA was extracted from 82 honey samples produced in Italy and amplified using two specific primer pairs that target the mitochondrial gene cytochrome oxidase I (COI) of A. tumida and two specific primer pairs that target the same gene in G. mellonella. The limit of detection was tested using sequential dilutions of the pest DNA. Only one honey sample produced in Calabria was positive for A. tumida whereas about 66% of all samples were positively amplified for G. mellonella. The use of honey eDNA could be important to establish early and effective measures to contain at the local (e.g., apiary) or regional scales these two damaging pests and, particularly for the small hive beetle, to prevent its widespread diffusion.

Application of Next Generation Semiconductor-Based Sequencing for the Identification of Apis mellifera Complementary Sex Determiner (csd) Alleles from Honey DNA

Simple Summary

Honey contains traces of the DNA of the honey bees that produced it. This environmental DNA can therefore be used to investigate the genome of the honey bees. In this study, we used a next generation sequencing technology to analyze the variability of a key gene of Apis mellifera L., the complementary sex determiner (csd) gene, using honey environmental DNA as a source of honey bee DNA. This gene determines the sex of the bees. Two different alleles at this locus are needed to produce females whereas males have only one copy of this gene as they are haploid. In case two identical alleles are present in a diploid individual, the larvae are not vital and are discarded by the workers. Therefore, there is an advantage in maintaining a large csd diversity in honey bee populations. In light of the recent decline in honey bee populations, it is important to monitor the allele variability at this gene. The applied methodology provided a new strategy to disclose the genetic diversity at the csd gene at the population-wide level and identify most, if not all, csd alleles present in the colonies in a single analysis.

Abstract

The complementary sex determiner (csd) gene plays an essential role in the sex determination of Apis mellifera L. Females develop only if fertilized eggs have functional heterozygous genotypes at this gene whereas males, being haploids, are hemizygous. Two identical csd alleles produce non vital males. In light of the recent decline in honey bee populations, it is therefore important to monitor the allele variability at this gene. In this study, we tested the application of next generation semiconductor-based sequencing technology (Ion Torrent) coupled with environmental honey DNA as a source of honey bee genome information to retrieve massive sequencing data for the analysis of variability at the hypervariable region (HVR) of the csd gene. DNA was extracted from 12 honey samples collected from honeycombs directly retrieved from 12 different colonies. A specifically designed bioinformatic pipeline, applied to analyze a total of about 1.5 million reads, identified a total of 160 different csd alleles, 55% of which were novel. The average number of alleles per sample was compatible with the number of expected patrilines per colony, according to the mating behavior of the queens. Allele diversity at the csd could also provide information useful to reconstruct the history of the honey.

Distribution of the Main Apis mellifera Mitochondrial DNA Lineages in Italy Assessed Using an Environmental DNA Approach

Growing interest has been emerging on the need to monitor the genetic integrity of the European Apis mellifera subspecies that could be threatened by the human-mediated dispersion of non-native populations and lines. Mitochondrial DNA (mtDNA) lineages can provide useful information for this purpose. In this study, we took advantage of the environmental DNA (eDNA) contained in the honey, which can be analyzed to detect the main groups of mitotypes of the honey bees that produced it. In this study, we applied this eDNA to produce a distribution map all over the Italian peninsula and the two major islands (Sicily and Sardinia) of the following three honey bee mtDNA lineages: A, C and M. A total of 607 georeferenced honey samples, produced in all Italian regions, was analyzed to detect these lineages. The A lineage was widespread in Sicily, as expected, considering that A. m. siciliana carries the African lineage. Surprisingly, this lineage was also reported in about 14% of all other samples produced in almost all continental regions, and in Sardinia. The applied method obtained an updated distribution map of honey bee mtDNA lineages that could be useful to design policies for the conservation of Italian honey bee genetic resources.

Analysis of honey environmental DNA indicates that the honey bee (Apis mellifera L.) trypanosome parasite Lotmaria passim is widespread in the apiaries of the North of Italy

Lotmaria passim is a trypanosomatid that infects honey bees. In this study, we established an axenic culture of L. passim from Italian isolates and then used its DNA as a control in subsequent analyses that investigated environmental DNA (eDNA) to detect this trypasonosomatid. The source of eDNA was honey, which has been already demonstrated to be useful to detect honey bee parasites. DNA from a total of 164 honey samples collected in the North of Italy was amplified with three L. passim specific PCR primers and 78% of the analysed samples gave positive results. These results indicated a high prevalence rate of this trypanosomatid in the North of Italy, where it might be considered another threat to honey bee health.

Honey as a Source of Environmental DNA for the Detection and Monitoring of Honey Bee Pathogens and Parasites

Environmental DNA (eDNA) has been proposed as a powerful tool to detect and monitor cryptic, elusive, or invasive organisms. We recently demonstrated that honey constitutes an easily accessible source of eDNA. In this study, we extracted DNA from 102 honey samples (74 from Italy and 28 from 17 other countries of all continents) and tested the presence of DNA of nine honey bee pathogens and parasites (Paenibacillus larvae, Melissococcus plutonius, Nosema apis, Nosema ceranae, Ascosphaera apis,Lotmaria passim, Acarapis woodi, Varroa destructor, and Tropilaelaps spp.) using qualitative PCR assays. All honey samples contained DNA from V. destructor, confirming the widespread diffusion of this mite. None of the samples gave positive amplifications for N. apis, A. woodi, and Tropilaelaps spp. M. plutonius was detected in 87% of the samples, whereas the other pathogens were detected in 43% to 57% of all samples. The frequency of Italian samples positive for P. larvae was significantly lower (49%) than in all other countries (79%). The co-occurrence of positive samples for L. passim and A. apis with N. ceranae was significant. This study demonstrated that honey eDNA can be useful to establish monitoring tools to evaluate the sanitary status of honey bee populations.

Shotgun sequencing of honey DNA can describe honey bee derived environmental signatures and the honey bee hologenome complexity

Honey bees are large-scale monitoring tools due to their extensive environmental exploration. In their activities and from the hive ecosystem complex, they get in close contact with many organisms whose traces can be transferred into the honey, which can represent an interesting reservoir of environmental DNA (eDNA) signatures and information useful to analyse the honey bee hologenome complexity. In this study, we tested a deep shotgun sequencing approach of honey DNA coupled with a specifically adapted bioinformatic pipeline. This methodology was applied to a few honey samples pointing out DNA sequences from 191 organisms spanning different kingdoms or phyla (viruses, bacteria, plants, fungi, protozoans, arthropods, mammals). Bacteria included the largest number of species. These multi-kingdom signatures listed common hive and honey bee gut microorganisms, honey bee pathogens, parasites and pests, which resembled a complex interplay that might provide a general picture of the honey bee pathosphere. Based on the Apis mellifera filamentous virus genome diversity (the most abundant detected DNA source) we obtained information that could define the origin of the honey at the apiary level. Mining Apis mellifera sequences made it possible to identify the honey bee subspecies both at the mitochondrial and nuclear genome levels.