They trained a group of bees to detect samples infected with SARS-CoV-2

Researchers from the Netherlands successfully trained one type of these insects to identify minks infected with the new coronavirus. What technique did they use

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According to the results of the study, "the diagnostic evaluation test shows that the tests using bees have a specificity of 86% and a sensitivity of 92%" (Getty)

The COVID-19 pandemic highlighted the need for rapid and reliable testing methods to detect new viral diseases, both in humans and animals.

The thing is Infections and other pathologies cause detectable physiological changes in the volatile organic compound (VOC) profile of animals and humans, and this profile also differs between healthy and infected individuals.

Thus, VOCs offer an odor fingerprint based on sex, age, diet, genetic history, and metabolic conditions, making the fingerprint unique to each individual. This fingerprint, when analyzed, provides relevant information about the individual’s health, prompting the development of a rapid VOC-based testing method.

With that information, Researchers from the Netherlands successfully trained Apis mellifera bees to identify minks infected with severe acute respiratory syndrome 2 (SARS-CoV-2). Using Pavlovian conditioning protocols, they quickly trained the insects to respond specifically to the odors of infected mink, highlighting the possibility of making bees part of a broader SARS-CoV-2 diagnostic system.

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The Current Standard For The Diagnosis Of Covid-19 Is The Detection Of Viral Rna From Respiratory Samples Using The Reverse Transcription Polymerase Chain Reaction, Better Known As Pcr (Efe).

According to the results of the study published on the bioRxiv prepress server, “The diagnostic evaluation test shows that the tests using bees have a specificity of 86% and a sensitivity of 92%.”

The researchers tested two different training protocols to assess the performance of the bees in terms of the learning rate, memory retention, and accuracy and developed a rapid, non-invasive test in which multiple bees are tested in parallel on the same samples to obtain reliable results on the health status of a subject.

With the help of the data obtained from the training experiments, they simulated a diagnostic evaluation test to calculate the potential efficacy of their diagnostic test.

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“We Suggest That A Bee-Based Diagnosis Can Offer A Rapid And Reliable Test,” Say The Researchers. (Getty)

We suggest that a bee-based diagnosis can offer a rapid and reliable test that provides a low-input addition to currently available test methods. -the authors assured in the publication-. A bee-based diagnostic test could be particularly relevant for remote and developing communities that lack the resources and infrastructure necessary for conventional testing methods. ”

As evidenced by the study results, bees alone have limited sensitivity and specificity in diagnosis, since the retention tests for protocol 2 show that 24 hours after conditioning, 67% of the bees correctly identified the infected sample (sensitivity), and 58% of the bees correctly identified the healthy sample (specificity). Therefore, the parallel use of several bees in the same sample can effectively improve the diagnostic performance. In that case, a diagnosis would be based on the reaction of a certain number of bees (called the diagnostic threshold) to the sample tested.

In summary, the findings of this study suggest that bees could be useful in the diagnosis of SARS-CoV-2 and potentially in the diagnosis of other infectious diseases.


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    Written by Christina d'souza

    Proofreader, editor, journalist. I have been doing my favourite thing for more than six years.

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