Dual‐fluorescence imaging and automated trophallaxis detection for studying multi‐nutrient regulation in superorganisms

Baltiansky, Lior; Sarafian‐Tamam, Einav; Greenwald, Efrat; Feinerman, Ofer

doi:10.1111/2041-210x.13646

Cited by 11 publications

(10 citation statements)

References 85 publications

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“…Overcoming this limitation will be facilitated by the ongoing development of techniques enabling the automated detection of specific social behaviours (e.g. trophallaxis [75,76]) and the study of their role in promoting or preventing disease spread [69].…”

Section: Discussionmentioning

confidence: 99%

Immune challenges increase network centrality in a queenless ant

et al. 2021

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Social animals display a wide range of behavioural defences against infectious diseases, some of which increase social contacts with infectious individuals (e.g. mutual grooming), while others decrease them (e.g. social exclusion). These defences often rely on the detection of infectious individuals, but this can be achieved in several ways that are difficult to differentiate. Here, we combine non-pathogenic immune challenges with automated tracking in colonies of the clonal raider ant to ask whether ants can detect the immune status of their social partners and to quantify their behavioural responses to this perceived infection risk. We first show that a key behavioural response elicited by live pathogens (allogrooming) can be qualitatively recapitulated by immune challenges alone. Automated scoring of interactions between all colony members reveals that this behavioural response increases the network centrality of immune-challenged individuals through a general increase in physical contacts. These results show that ants can detect the immune status of their nest-mates and respond with a general ‘caring’ strategy, rather than avoidance, towards social partners that are perceived to be infectious. Finally, we find no evidence that changes in cuticular hydrocarbon profiles drive these behavioural effects.

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Section: Discussionmentioning

confidence: 99%

Immune challenges increase network centrality in a queenless ant

et al. 2021

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“…Performance measurements (Table 1 ) showed that our trophallaxis detector outperforms the state of the art 8 , 24 . Its Matthews correlation coefficient (MCC) is 0.89, 0.28 higher than that of the best automatic honey bee trophallaxis detector so far 8 .…”

Section: Resultsmentioning

confidence: 99%

“…1 ). Previously described automatic trophallaxis detectors are either unable to determine the direction of liquid transfer 8 , 9 , 23 or require fluorescence-labeled liquids and a more complex tracking system to do so 24 . To establish the liquid transfer direction directly from videos, we trained a second CNN (Supplementary Table 1 and Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Complementing the innovations in ref. 23 , 24 , our key contribution lies in combining tracking information, such as an animal’s location and orientation, with domain knowledge about the behavior of interest to perform a precise yet computationally inexpensive region proposal that acts as an attention mechanism for the CNN. In addition, we leverage information from the barcodes to simplify the behavior classification task by rotating the proposed image regions to correspond to a predefined reference frame.…”

Section: Introductionmentioning

confidence: 99%

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Automated monitoring of honey bees with barcodes and artificial intelligence reveals two distinct social networks from a single affiliative behavior

Gernat

Jagla

Jones

et al. 2023

Sci Rep

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Barcode-based tracking of individuals is revolutionizing animal behavior studies, but further progress hinges on whether in addition to determining an individual’s location, specific behaviors can be identified and monitored. We achieve this goal using information from the barcodes to identify tightly bounded image regions that potentially show the behavior of interest. These image regions are then analyzed with convolutional neural networks to verify that the behavior occurred. When applied to a challenging test case, detecting social liquid transfer (trophallaxis) in the honey bee hive, this approach yielded a 67% higher sensitivity and an 11% lower error rate than the best detector for honey bee trophallaxis so far. We were furthermore able to automatically detect whether a bee donates or receives liquid, which previously required manual observations. By applying our trophallaxis detector to recordings from three honey bee colonies and performing simulations, we discovered that liquid exchanges among bees generate two distinct social networks with different transmission capabilities. Finally, we demonstrate that our approach generalizes to detecting other specific behaviors. We envision that its broad application will enable automatic, high-resolution behavioral studies that address a broad range of previously intractable questions in evolutionary biology, ethology, neuroscience, and molecular biology.

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“…Trophallaxis is an efficient mechanism for the rapid transfer of nutrients among all colony members [24][25][26][27] . To date, food dyes 28,29 , radioactive-labeled food 24,26,[30][31][32][33] , and, recently, fluorescent-dyed food 34,35 , have been used to study the path of resources transferred via trophallaxis in hymenopterans. While these methods have provided valuable information on the food exchange dynamics within the colony, they are limited by the constraints of labeling the food resources as a whole.…”

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confidence: 99%

Continuous exchange of nectar nutrients in an Oriental hornet colony

2022

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Nutritional exchanges play a fundamental role in the evolution of animal societies. In higher animal societies, while adult individuals can be both food donors and receivers, the offspring usually only receive food from the adults. Hornets and wasps are fierce insect hunters that feed their larvae with prey. However, although the adults also consume floral nectar, the role of nectar in vespid nutrition has remained largely unknown. We provided experimental colonies of the Oriental hornet with artificial nectar enriched with a 13C-labeled amino acid, and found that a continuous cycle of nutrition took place, in which nectar nutrients were used and exchanged back and forth between adults and larvae. We posit that this continuous cycle of nutrients constitutes a mechanism contributing to social cohesion. In an additional experiment, we found that nectar consumption was essential for adult and larval survival, suggesting the importance of wasps and hornets as pollinators in natural ecosystems.

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Dual‐fluorescence imaging and automated trophallaxis detection for studying multi‐nutrient regulation in superorganisms

Abstract: This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as

Cited by 11 publications

References 85 publications

Immune challenges increase network centrality in a queenless ant

Immune challenges increase network centrality in a queenless ant

Automated monitoring of honey bees with barcodes and artificial intelligence reveals two distinct social networks from a single affiliative behavior

Continuous exchange of nectar nutrients in an Oriental hornet colony

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