Vector‐borne pathogens exist in obligate transmission cycles between vector and reservoir host species. Host and vector shifts can lead to geographic expansion of infectious agents and the emergence of new diseases in susceptible individuals. Three bacterial genospecies (Borrelia afzelii, Borrelia bavariensis, and Borrelia garinii) predominantly utilize two distinct tick species as vectors in Asia (Ixodes persulcatus) and Europe (Ixodes ricinus). Through these vectors, the bacteria can infect various vertebrate groups (e.g., rodents, birds) including humans where they cause Lyme borreliosis, the most common vector‐borne disease in the Northern hemisphere. Yet, how and in which order the three Borrelia genospecies colonized each continent remains unclear including the evolutionary consequences of this geographic expansion. Here, by reconstructing the evolutionary history of 142 Eurasian isolates, we found evidence that the ancestors of each of the three genospecies probably have an Asian origin. Even so, each genospecies studied displayed a unique substructuring and evolutionary response to the colonization of Europe. The pattern of allele sharing between continents is consistent with the dispersal rate of the respective vertebrate hosts, supporting the concept that adaptation of Borrelia genospecies to the host is important for pathogen dispersal. Our results highlight that Eurasian Lyme borreliosis agents are all capable of geographic expansion with host association influencing their dispersal; further displaying the importance of host and vector association to the geographic expansion of vector‐borne pathogens and potentially conditioning their capacity as emergent pathogens.
Over the past few decades, several investigations around the globe have reported alarming declines in the abundance and diversity of bee species. The success of effective conservation strategies targeting these important pollinators relies heavily on accurate biodiversity assessments. The shortage of taxonomic experts and the escalation of the ongoing biodiversity crisis call for the development of alternative identification tools to implement efficient monitoring programs. The validation of such techniques is crucial to ensure that they provide results comparable to those of traditional morphotaxonomy. Here we performed two double-blind experiments to evaluate the accuracy of a pair of new techniques used for wild bee identification: DNA metabarcoding and in vivo identification in the field. The methods were tested on sets of wild bees from Germany and their results compared against evaluations done by panels of bee experts using traditional morphotaxonomy. On average the congruency of species identification between metabarcoding and morphotaxonomy was 88.98% across samples (N = 10), while in vivo identification and morphotaxonomy were 91.81% congruent (N = 7) for bees considered feasible for in vivo identification in the field. Traditional morphotaxonomy showed similar congruencies when compared to itself: 93.65% in the metabarcoding study and 92.96% in the in vivo study. Overall, these results support both new methods as viable alternatives to traditional microscopy-based assessment, with neither method being error-free. Metabarcoding provides a suitable option to analyze large numbers of specimens in the absence of highly trained taxonomic experts, while in vivo identification is recommended for repeated long-term monitoring, and when working in areas where the sampling of individuals could threaten local populations of endangered wild bee species. Further research is still needed to explore the potential of both techniques for conservation management and wildlife monitoring, as well as to overcome their current limitations as taxonomic tools.
Museums and other institutions curating natural history collections (NHCs) are fundamental entities to many scientific disciplines, as they house data and reference material for varied research projects. As such, biological specimens preserved in NHCs represent accessible physical records of the living world's history. They provide useful information regarding the presence and distribution of different taxonomic groups through space and time. Despite the importance of biological museum specimens, their potential to answer scientific questions, pertinent to the necessities of our current historical context, is often under-explored. The currently-known wild bee fauna of Luxembourg comprises 341 registered species distributed amongst 38 different genera. However, specimens stored in the archives of local NHCs represent an untapped resource to update taxonomic lists, including potentially overlooked findings relevant to the development of national conservation strategies. We re-investigated the wild bee collection of the Zoology Department of the National Museum of Natural History Luxembourg by using morphotaxonomy and DNA barcoding. The collection revision led to the discovery of four species so far not described for the country: Andrena lagopus (Latreille, 1809), Nomada furva (Panzer, 1798), Hoplitis papaveris (Latreille, 1799) and Sphecodes majalis (Pérez, 1903). Additionally, the presence of Nomada sexfasciata (Panzer, 1799), which inexplicably had been omitted by the most current species list, can be re-confirmed. Altogether, our findings increase the number of recorded wild bee species in Luxembourg to 346. Moreover, the results highlight the crucial role of NHCs as repositories of our knowledge of the natural world.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.