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Dynafor au Congrès APIMONDIA 2023 (Santiago du Chili)

Du 4 au 9 Septembre se tenait la 48ième édition du congrès mondial sur les abeilles. Pour en savoir plus:

Il réunissait plus de 400 participants : scientifiques, professionnels de l’apiculture, acteurs du monde rural, gestionnaire de réserves naturelles etc ..A côte des sessions dédiées à la santé des abeilles (résistance au varroa, qualité nutritionnelle des pollens et nectar etc) des projets orientés vers une apiculture durable intégrant biodiversité et tradition rurale ont été présentés. A cette occasion Magalie Pichon (DYNAFOR) et Kamila Tabet (GENPHYSE) ont présenté trois posters et deux communications orales sur les approches utilisant la biologie moléculaire pour identifier les abeilles sauvages ou pour caractériser les populations d’abeilles mellifères.

Au programme également dégustation de miels provenant de différents continents, Amérique du Sud, Afrique, Nouvelle-Zélande etc ... et découverte de la plus petite espèces d’abeilles du monde Leurotrigona muelleri qui vit au Pérou.

Voilà les informations sur les posters de Dynafor:

1°) Construction of a 16S mini barcode library for french wild bees

Magalie Pichon, Alain Vignal, Emmanuelle Labarthe, Nathalie Escaravage, Geraldine Pascal, Christophe Klopp, André Pornon, Rémi Rudelle, Annie Ouin, Mélodie Ollivier, Kamila Canale Tabet

The use of molecular biology tools: barcoding/metabarcoding is particularly attractive and complementary to conventional methods for studying biodiversity. For wild bees, the development of DNA barcodes has been carried out in Canada and in various European countries (Germany, UK, Switzerland, etc.). In France, a national project CODABEILLES, has been initiated in 2021 to barcode the 968 species listed. Most barcoding and metabarcoding experiments on wild bees have been performed using 650 bps of the CO1 gene. Despite high amplification and sequencing success (about 70%) for most bee’s families, some genera like Andrena, or old specimens from collections are difficult or even impossible to amplify with classical Folmer primers. In the present work, we have built a 16S (250 bp) mini DNA-barcode database. Data come from a regional collection of French wild bees that contains about 8000 individuals belonging to 174 species and 21 genera previously identified by taxonomists. The specimens had been sampled between 2013 and 2020 using pan traps or sweep nets and kept dried in the collection. DNA was extracted from front legs (one to three individuals per species) and sequenced using MiSeq and Sanger technologies. All mini-barcodes were then validated by distance tree inference. To assess the discrimination strength metabarcoding we have manually mix 3, 5, or 14 legs in variable proportion corresponding to intraspecies or interspecies bees. We demonstrated that the 16S mini barcode is well adapted to delineate wild bee species, particularly whenever CO1 is unsuccessful. Moreover, this mini barcode should be useful to perform low-cost metabarcoding and therefore opens opportunities for environmental DNA approaches by analysis of the traces left on foraged flowers.

2°) Identification of wild and domestic bees by non-destructive molecular methods

Magalie Pichon, Mélodie Ollivier, Elisa Simon, Emmanuelle Labarthe, Alain Vignal, Christophe Klopp, Annie Ouin, Kamila Canale Tabet

The study of insect pollinator communities is at the heart of a great paradox: today, characterizing the diversity of these species implies sacrificing them (trapping and then morphological identification). Methods based on the amputation of a member (segment of antennae, piece of wings or legs) have been used in honey bees (Madella et al., 2021) or bumblebees (Holehouse et al., 2003) but they lead to mortality rates depending on the size of the specimens. Recently, different laboratories around the world are mobilizing to try to develop new non-lethal identification methods such as acoustics (Heise et al., 2020), deep learning: mathematical algorithms capable of identifying specimens from insect photos (Høye et al., 2021), and sampling from faeces (Scriven et al., 2013). At the same time, with rapid advances in sequencing methods, environmental DNA-based approaches (i.e., identification of individuals from traces left in the environment) have opened up promising prospects for inventorying aquatic or terrestrial biodiversity while preserving the integrity of specimens (Banerjee et al., 2022). We proposed to develop a non-lethal protocol to identify wild bees from the traces they can leave while foraging on flowers. It is based on the enclosure or exposure to the open air of strawberry plants and the collection of flowers for the extraction of insect DNA traces. The experimental protocol is composed of 4 strawberry plants placed in 3 conditions: a cage with insects, a cage without insects and exposed to the open air. Initially we extracted DNA from insect tracks left on flowers only in the "bees introduced into the enclosure" condition and by testing two types of extraction kits. The extracted DNAs were then amplified by PCR with the insect 16S minibarcode (Clarke et al., 2014). We had previously constructed a barcode baseline for wild bees with this minibarcode (results in publication). Several PCR conditions allowed us to select the DNA Extraction Kit that yielded sequencable amplifiates. Sequencing of 4 samples (2 duplicates) and bioinformatics processing of the data allowed us to find the sequences of the bees that were introduced but also sequences corresponding to 16S DNA of strawberry plants.


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