[{"oa":1,"quality_controlled":"1","publisher":"National Academy of Sciences","year":"2017","publication":"PNAS","day":"03","page":"E5396 - E5405","date_created":"2018-12-11T11:48:00Z","date_published":"2017-07-03T00:00:00Z","doi":"10.1073/pnas.1702020114","citation":{"ista":"Veller C, Hayward L, Nowak M, Hilbe C. 2017. The red queen and king in finite populations. PNAS. 114(27), E5396–E5405.","chicago":"Veller, Carl, Laura Hayward, Martin Nowak, and Christian Hilbe. “The Red Queen and King in Finite Populations.” PNAS. National Academy of Sciences, 2017. https://doi.org/10.1073/pnas.1702020114.","apa":"Veller, C., Hayward, L., Nowak, M., & Hilbe, C. (2017). The red queen and king in finite populations. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1702020114","ama":"Veller C, Hayward L, Nowak M, Hilbe C. The red queen and king in finite populations. PNAS. 2017;114(27):E5396-E5405. doi:10.1073/pnas.1702020114","short":"C. Veller, L. Hayward, M. Nowak, C. Hilbe, PNAS 114 (2017) E5396–E5405.","ieee":"C. Veller, L. Hayward, M. Nowak, and C. Hilbe, “The red queen and king in finite populations,” PNAS, vol. 114, no. 27. National Academy of Sciences, pp. E5396–E5405, 2017.","mla":"Veller, Carl, et al. “The Red Queen and King in Finite Populations.” PNAS, vol. 114, no. 27, National Academy of Sciences, 2017, pp. E5396–405, doi:10.1073/pnas.1702020114."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","external_id":{"pmid":["28630336"]},"publist_id":"7002","author":[{"last_name":"Veller","full_name":"Veller, Carl","first_name":"Carl"},{"full_name":"Hayward, Laura","last_name":"Hayward","first_name":"Laura"},{"last_name":"Nowak","full_name":"Nowak, Martin","first_name":"Martin"},{"id":"2FDF8F3C-F248-11E8-B48F-1D18A9856A87","first_name":"Christian","last_name":"Hilbe","full_name":"Hilbe, Christian","orcid":"0000-0001-5116-955X"}],"title":"The red queen and king in finite populations","abstract":[{"lang":"eng","text":"In antagonistic symbioses, such as host–parasite interactions, one population’s success is the other’s loss. In mutualistic symbioses, such as division of labor, both parties can gain, but they might have different preferences over the possible mutualistic arrangements. The rates of evolution of the two populations in a symbiosis are important determinants of which population will be more successful: Faster evolution is thought to be favored in antagonistic symbioses (the “Red Queen effect”), but disfavored in certain mutualistic symbioses (the “Red King effect”). However, it remains unclear which biological parameters drive these effects. Here, we analyze the effects of the various determinants of evolutionary rate: generation time, mutation rate, population size, and the intensity of natural selection. Our main results hold for the case where mutation is infrequent. Slower evolution causes a long-term advantage in an important class of mutualistic interactions. Surprisingly, less intense selection is the strongest driver of this Red King effect, whereas relative mutation rates and generation times have little effect. In antagonistic interactions, faster evolution by any means is beneficial. Our results provide insight into the demographic evolution of symbionts. "}],"oa_version":"Submitted Version","pmid":1,"main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5502615/"}],"scopus_import":1,"intvolume":" 114","month":"07","publication_status":"published","publication_identifier":{"issn":["00278424"]},"language":[{"iso":"eng"}],"issue":"27","volume":114,"_id":"699","type":"journal_article","status":"public","date_updated":"2021-01-12T08:11:21Z","department":[{"_id":"KrCh"}]},{"abstract":[{"text":"Individual computations and social interactions underlying collective behavior in groups of animals are of great ethological, behavioral, and theoretical interest. While complex individual behaviors have successfully been parsed into small dictionaries of stereotyped behavioral modes, studies of collective behavior largely ignored these findings; instead, their focus was on inferring single, mode-independent social interaction rules that reproduced macroscopic and often qualitative features of group behavior. Here, we bring these two approaches together to predict individual swimming patterns of adult zebrafish in a group. We show that fish alternate between an “active” mode, in which they are sensitive to the swimming patterns of conspecifics, and a “passive” mode, where they ignore them. Using a model that accounts for these two modes explicitly, we predict behaviors of individual fish with high accuracy, outperforming previous approaches that assumed a single continuous computation by individuals and simple metric or topological weighing of neighbors’ behavior. At the group level, switching between active and passive modes is uncorrelated among fish, but correlated directional swimming behavior still emerges. Our quantitative approach for studying complex, multi-modal individual behavior jointly with emergent group behavior is readily extensible to additional behavioral modes and their neural correlates as well as to other species.","lang":"eng"}],"oa_version":"Submitted Version","pmid":1,"scopus_import":1,"main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5617265/"}],"month":"09","intvolume":" 114","publication_identifier":{"issn":["00278424"]},"publication_status":"published","language":[{"iso":"eng"}],"issue":"38","volume":114,"_id":"725","type":"journal_article","status":"public","date_updated":"2021-01-12T08:12:36Z","department":[{"_id":"GaTk"}],"quality_controlled":"1","publisher":"National Academy of Sciences","oa":1,"year":"2017","day":"19","publication":"PNAS","page":"10149 - 10154","date_published":"2017-09-19T00:00:00Z","doi":"10.1073/pnas.1703817114","date_created":"2018-12-11T11:48:10Z","citation":{"ista":"Harpaz R, Tkačik G, Schneidman E. 2017. Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. 114(38), 10149–10154.","chicago":"Harpaz, Roy, Gašper Tkačik, and Elad Schneidman. “Discrete Modes of Social Information Processing Predict Individual Behavior of Fish in a Group.” PNAS. National Academy of Sciences, 2017. https://doi.org/10.1073/pnas.1703817114.","apa":"Harpaz, R., Tkačik, G., & Schneidman, E. (2017). Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1703817114","ama":"Harpaz R, Tkačik G, Schneidman E. Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. 2017;114(38):10149-10154. doi:10.1073/pnas.1703817114","short":"R. Harpaz, G. Tkačik, E. Schneidman, PNAS 114 (2017) 10149–10154.","ieee":"R. Harpaz, G. Tkačik, and E. Schneidman, “Discrete modes of social information processing predict individual behavior of fish in a group,” PNAS, vol. 114, no. 38. National Academy of Sciences, pp. 10149–10154, 2017.","mla":"Harpaz, Roy, et al. “Discrete Modes of Social Information Processing Predict Individual Behavior of Fish in a Group.” PNAS, vol. 114, no. 38, National Academy of Sciences, 2017, pp. 10149–54, doi:10.1073/pnas.1703817114."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Roy","last_name":"Harpaz","full_name":"Harpaz, Roy"},{"orcid":"0000-0002-6699-1455","full_name":"Tkacik, Gasper","last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gasper"},{"first_name":"Elad","full_name":"Schneidman, Elad","last_name":"Schneidman"}],"publist_id":"6953","external_id":{"pmid":["28874581"]},"title":"Discrete modes of social information processing predict individual behavior of fish in a group"},{"year":"2017","isi":1,"publication":"PNAS","day":"03","page":"10666 - 10671","date_created":"2018-12-11T11:48:41Z","doi":"10.1073/pnas.1713372114","date_published":"2017-10-03T00:00:00Z","oa":1,"publisher":"National Academy of Sciences","quality_controlled":"1","citation":{"chicago":"Vos, Marjon de, Marcin P Zagórski, Alan Mcnally, and Mark Tobias Bollenbach. “Interaction Networks, Ecological Stability, and Collective Antibiotic Tolerance in Polymicrobial Infections.” PNAS. National Academy of Sciences, 2017. https://doi.org/10.1073/pnas.1713372114.","ista":"de Vos M, Zagórski MP, Mcnally A, Bollenbach MT. 2017. Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections. PNAS. 114(40), 10666–10671.","mla":"de Vos, Marjon, et al. “Interaction Networks, Ecological Stability, and Collective Antibiotic Tolerance in Polymicrobial Infections.” PNAS, vol. 114, no. 40, National Academy of Sciences, 2017, pp. 10666–71, doi:10.1073/pnas.1713372114.","ieee":"M. de Vos, M. P. Zagórski, A. Mcnally, and M. T. Bollenbach, “Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections,” PNAS, vol. 114, no. 40. National Academy of Sciences, pp. 10666–10671, 2017.","short":"M. de Vos, M.P. Zagórski, A. Mcnally, M.T. Bollenbach, PNAS 114 (2017) 10666–10671.","apa":"de Vos, M., Zagórski, M. P., Mcnally, A., & Bollenbach, M. T. (2017). Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1713372114","ama":"de Vos M, Zagórski MP, Mcnally A, Bollenbach MT. Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections. PNAS. 2017;114(40):10666-10671. doi:10.1073/pnas.1713372114"},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","external_id":{"isi":["000412130500061"],"pmid":["28923953"]},"article_processing_charge":"No","author":[{"id":"3111FFAC-F248-11E8-B48F-1D18A9856A87","first_name":"Marjon","last_name":"De Vos","full_name":"De Vos, Marjon"},{"last_name":"Zagórski","orcid":"0000-0001-7896-7762","full_name":"Zagórski, Marcin P","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","first_name":"Marcin P"},{"first_name":"Alan","last_name":"Mcnally","full_name":"Mcnally, Alan"},{"id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","first_name":"Mark Tobias","last_name":"Bollenbach","full_name":"Bollenbach, Mark Tobias","orcid":"0000-0003-4398-476X"}],"publist_id":"6827","title":"Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections","project":[{"name":"Optimality principles in responses to antibiotics","grant_number":"303507","call_identifier":"FP7","_id":"25E83C2C-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FWF","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","grant_number":"P27201-B22","name":"Revealing the mechanisms underlying drug interactions"}],"publication_status":"published","publication_identifier":{"issn":["00278424"]},"language":[{"iso":"eng"}],"ec_funded":1,"volume":114,"issue":"40","abstract":[{"lang":"eng","text":"Polymicrobial infections constitute small ecosystems that accommodate several bacterial species. Commonly, these bacteria are investigated in isolation. However, it is unknown to what extent the isolates interact and whether their interactions alter bacterial growth and ecosystem resilience in the presence and absence of antibiotics. We quantified the complete ecological interaction network for 72 bacterial isolates collected from 23 individuals diagnosed with polymicrobial urinary tract infections and found that most interactions cluster based on evolutionary relatedness. Statistical network analysis revealed that competitive and cooperative reciprocal interactions are enriched in the global network, while cooperative interactions are depleted in the individual host community networks. A population dynamics model parameterized by our measurements suggests that interactions restrict community stability, explaining the observed species diversity of these communities. We further show that the clinical isolates frequently protect each other from clinically relevant antibiotics. Together, these results highlight that ecological interactions are crucial for the growth and survival of bacteria in polymicrobial infection communities and affect their assembly and resilience. "}],"oa_version":"Submitted Version","pmid":1,"main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635929/"}],"scopus_import":"1","intvolume":" 114","month":"10","date_updated":"2023-09-26T16:18:48Z","department":[{"_id":"ToBo"}],"_id":"822","type":"journal_article","status":"public"}]