Bees can be trained to identify SARS-CoV-2 infected samples

Autor: Aurore Avarguès-Weber, Jose L. Gonzales, Renate W. Hakze-van der Honing, Alexander Haverkamp, Marcel Dicke, J. Priem, Evangelos Kontos, Aria Samimi, Wim H.M. van der Poel
Přispěvatelé: Wageningen University and Research [Wageningen] (WUR), Centre de Recherches sur la Cognition Animale - UMR5169 (CRCA), Institut des sciences du cerveau de Toulouse. (ISCT), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre de Biologie Intégrative (CBI), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre de Biologie Intégrative (CBI), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre de Biologie Intégrative (CBI), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Toulouse Mind & Brain Institut (TMBI), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, Avarguès-Weber, Aurore, Centre de Recherches sur la Cognition Animale (CRCA), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut des sciences du cerveau de Toulouse. (ISCT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J)-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Epidemiology
[SDV]Life Sciences [q-bio]
Diagnostic evaluation
computer.software_genre
[SCCO]Cognitive science
[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases
Laboratory of Entomology
[SDV.MHEP.ME] Life Sciences [q-bio]/Human health and pathology/Emerging diseases
0303 health sciences
[SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases
Diagnostic test
Memory retention
Bees
PE&RC
Virology & Molecular Biology
Detection
[SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases
General Agricultural and Biological Sciences
Covid-19
2019-20 coronavirus outbreak
Coronavirus disease 2019 (COVID-19)
Bioinformatica & Diermodellen
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Biology
Machine learning
Diagnostic system
General Biochemistry
Genetics and Molecular Biology
Honeybees
03 medical and health sciences
Bio-informatics & Animal models
Animals
Humans
Learning
Epidemiology
Bio-informatics & Animal models
Pandemics
030304 developmental biology
Epidemiologie
[SDV.BA.MVSA]Life Sciences [q-bio]/Animal biology/Veterinary medicine and animal Health
030306 microbiology
business.industry
SARS-CoV-2
[SDV.BA.MVSA] Life Sciences [q-bio]/Animal biology/Veterinary medicine and animal Health
[SCCO] Cognitive science
Laboratorium voor Entomologie
Olfaction
Virologie & Moleculaire Biologie
[SDV.BA.ZI]Life Sciences [q-bio]/Animal biology/Invertebrate Zoology
Epidemiologie
Bioinformatica & Diermodellen
Odorants
SARS-CoV2
[SDV.BA.ZI] Life Sciences [q-bio]/Animal biology/Invertebrate Zoology
Artificial intelligence
EPS
business
computer
Conditioning
Zdroj: Biology Open, 11(4)
Biology Open
Biology Open, 2022, 11 (4), pp.bio059111. ⟨10.1242/bio.059111⟩
Biology Open 11 (2022) 4
ISSN: 2046-6390
DOI: 10.1242/bio.059111⟩
Popis: The COVID-19 pandemic has illustrated the need for the development of fast and reliable testing methods for novel, zoonotic, viral diseases in both humans and animals. Pathologies lead to detectable changes in the Volatile Organic Compound (VOC) profile of animals, which can be monitored, thus allowing the development of a rapid VOC-based test. In the current study, we successfully trained honeybees (Apis mellifera) to identify SARS-CoV-2 infected minks (Neovison vison) thanks to Pavlovian conditioning protocols. The bees can be quickly conditioned to respond specifically to infected mink’s odours and could therefore be part of a wider SARS-CoV-2 diagnostic system. We tested two different training protocols to evaluate their performance in terms of learning rate, accuracy and memory retention. We designed a non-invasive rapid test in which multiple bees are tested in parallel on the same samples. This provided reliable results regarding a subject’s health status. Using the data from the training experiments, we simulated a diagnostic evaluation trial to predict the potential efficacy of our diagnostic test, which yielded a diagnostic sensitivity of 92% and specificity of 86%. We suggest that a honeybee-based diagnostics can offer a reliable and rapid test that provides a readily available, low-input addition to the currently available testing methods. A honeybee-based diagnostic test might be particularly relevant for remote and developing communities that lack the resources and infrastructure required for mainstream testing methods.
Databáze: OpenAIRE
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