Behavioral fingerprints predict insecticide and anthelmintic mode of action
Abstract Novel invertebrate‐killing compounds are required in agriculture and medicine to overcome resistance to existing treatments. Because insecticides and anthelmintics are discovered in phenotypic screens, a crucial step in the discovery process is determining the mode of action of hits. Visibl...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Springer Nature
2021-05-01
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| Series: | Molecular Systems Biology |
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| Online Access: | https://doi.org/10.15252/msb.202110267 |
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| _version_ | 1846121727866699776 |
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| author | Adam McDermott‐Rouse Eleni Minga Ida Barlow Luigi Feriani Philippa H Harlow Anthony J Flemming André E X Brown |
| author_facet | Adam McDermott‐Rouse Eleni Minga Ida Barlow Luigi Feriani Philippa H Harlow Anthony J Flemming André E X Brown |
| author_sort | Adam McDermott‐Rouse |
| collection | DOAJ |
| description | Abstract Novel invertebrate‐killing compounds are required in agriculture and medicine to overcome resistance to existing treatments. Because insecticides and anthelmintics are discovered in phenotypic screens, a crucial step in the discovery process is determining the mode of action of hits. Visible whole‐organism symptoms are combined with molecular and physiological data to determine mode of action. However, manual symptomology is laborious and requires symptoms that are strong enough to see by eye. Here, we use high‐throughput imaging and quantitative phenotyping to measure Caenorhabditiselegans behavioral responses to compounds and train a classifier that predicts mode of action with an accuracy of 88% for a set of ten common modes of action. We also classify compounds within each mode of action to discover substructure that is not captured in broad mode‐of‐action labels. High‐throughput imaging and automated phenotyping could therefore accelerate mode‐of‐action discovery in invertebrate‐targeting compound development and help to refine mode‐of‐action categories. |
| format | Article |
| id | doaj-art-7f6f11a769624a6cac0239709f443cfd |
| institution | Kabale University |
| issn | 1744-4292 |
| language | English |
| publishDate | 2021-05-01 |
| publisher | Springer Nature |
| record_format | Article |
| series | Molecular Systems Biology |
| spelling | doaj-art-7f6f11a769624a6cac0239709f443cfd2024-12-15T12:13:52ZengSpringer NatureMolecular Systems Biology1744-42922021-05-0117511410.15252/msb.202110267Behavioral fingerprints predict insecticide and anthelmintic mode of actionAdam McDermott‐Rouse0Eleni Minga1Ida Barlow2Luigi Feriani3Philippa H Harlow4Anthony J Flemming5André E X Brown6MRC London Institute of Medical SciencesMRC London Institute of Medical SciencesMRC London Institute of Medical SciencesMRC London Institute of Medical SciencesSyngenta, Jealott's Hill International Research CentreSyngenta, Jealott's Hill International Research CentreMRC London Institute of Medical SciencesAbstract Novel invertebrate‐killing compounds are required in agriculture and medicine to overcome resistance to existing treatments. Because insecticides and anthelmintics are discovered in phenotypic screens, a crucial step in the discovery process is determining the mode of action of hits. Visible whole‐organism symptoms are combined with molecular and physiological data to determine mode of action. However, manual symptomology is laborious and requires symptoms that are strong enough to see by eye. Here, we use high‐throughput imaging and quantitative phenotyping to measure Caenorhabditiselegans behavioral responses to compounds and train a classifier that predicts mode of action with an accuracy of 88% for a set of ten common modes of action. We also classify compounds within each mode of action to discover substructure that is not captured in broad mode‐of‐action labels. High‐throughput imaging and automated phenotyping could therefore accelerate mode‐of‐action discovery in invertebrate‐targeting compound development and help to refine mode‐of‐action categories.https://doi.org/10.15252/msb.202110267anthelminticsC.eleganscomputational ethologypesticidephenotypic screen |
| spellingShingle | Adam McDermott‐Rouse Eleni Minga Ida Barlow Luigi Feriani Philippa H Harlow Anthony J Flemming André E X Brown Behavioral fingerprints predict insecticide and anthelmintic mode of action Molecular Systems Biology anthelmintics C.elegans computational ethology pesticide phenotypic screen |
| title | Behavioral fingerprints predict insecticide and anthelmintic mode of action |
| title_full | Behavioral fingerprints predict insecticide and anthelmintic mode of action |
| title_fullStr | Behavioral fingerprints predict insecticide and anthelmintic mode of action |
| title_full_unstemmed | Behavioral fingerprints predict insecticide and anthelmintic mode of action |
| title_short | Behavioral fingerprints predict insecticide and anthelmintic mode of action |
| title_sort | behavioral fingerprints predict insecticide and anthelmintic mode of action |
| topic | anthelmintics C.elegans computational ethology pesticide phenotypic screen |
| url | https://doi.org/10.15252/msb.202110267 |
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