Social network plasticity decreases disease transmission in a eusocial insect

Protecting the colony When we get a cold and then stay home from work, we are not only taking care of ourselves but also protecting others. Such changes in behavior after infection are predicted in social animals but are difficult to quantify. Stroeymeyt et al. looked for such changes in the black garden ant and found that infected workers did alter their behavior—and healthy workers altered their behavior toward the sick. The changed behavior was especially valuable for protecting the most important and vulnerable members of the colony. Science, this issue p. 941 Sick black garden ants modify their behavior to protect the colony. Animal social networks are shaped by multiple selection pressures, including the need to ensure efficient communication and functioning while simultaneously limiting disease transmission. Social animals could potentially further reduce epidemic risk by altering their social networks in the presence of pathogens, yet there is currently no evidence for such pathogen-triggered responses. We tested this hypothesis experimentally in the ant Lasius niger using a combination of automated tracking, controlled pathogen exposure, transmission quantification, and temporally explicit simulations. Pathogen exposure induced behavioral changes in both exposed ants and their nestmates, which helped contain the disease by reinforcing key transmission-inhibitory properties of the colony’s contact network. This suggests that social network plasticity in response to pathogens is an effective strategy for mitigating the effects of disease in social groups.

[1]  Erik M. Volz,et al.  Correction: Effects of Heterogeneous and Clustered Contact Patterns on Infectious Disease Dynamics , 2011, PLoS Computational Biology.

[2]  Hae-Young Kim Statistical notes for clinical researchers: assessing normal distribution (2) using skewness and kurtosis , 2013, Restorative dentistry & endodontics.

[3]  C. Schweizer,et al.  Distribution of insect pathogenic soil fungi in Switzerland with special reference to Beauveria brongniartii and Metharhizium anisopliae , 2003, BioControl.

[4]  A. Read,et al.  Can fungal biopesticides control malaria? , 2007, Nature Reviews Microbiology.

[5]  M. Newman,et al.  Mixing patterns in networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[6]  Fabian J Theis,et al.  Social Transfer of Pathogenic Fungus Promotes Active Immunisation in Ant Colonies , 2012, PLoS biology.

[7]  W. H. Whitcomb,et al.  Artificial diet for rearing various species of ants. , 1970 .

[8]  J. Heinze,et al.  Ant queens increase their reproductive efforts after pathogen infection , 2017, Royal Society Open Science.

[9]  A. Crespi,et al.  Tracking Individuals Shows Spatial Fidelity Is a Key Regulator of Ant Social Organization , 2013, Science.

[10]  J. Deneubourg,et al.  Foraging recruitment inLeptothorax unifasciatus: The influence of foraging area familiarity and the age of the nest-site , 1986, Insectes Sociaux.

[11]  Alessandro Vespignani,et al.  The Architecture of Complex Weighted Networks: Measurements and Models , 2007 .

[12]  C. Lei,et al.  Experimental verification and molecular basis of active immunization against fungal pathogens in termites , 2015, Scientific Reports.

[13]  R. Rosenthal Combining results of independent studies. , 1978 .

[14]  S. Cremer,et al.  Social Immunity: Emergence and Evolution of Colony-Level Disease Protection. , 2018, Annual review of entomology.

[15]  Eric R. Pianka,et al.  On r- and K-Selection , 1970, The American Naturalist.

[16]  Alessandro Vespignani,et al.  Dynamical Patterns of Epidemic Outbreaks in Complex Heterogeneous Networks , 1999 .

[17]  J. Traniello Comparative foraging ecology of north temperate ants: The role of worker size and cooperative foraging in prey selection , 1987, Insectes Sociaux.

[18]  Bartosz Walter,et al.  Moribund Ants Leave Their Nests to Die in Social Isolation , 2010, Current Biology.

[19]  Luis E C Rocha,et al.  Information dynamics shape the sexual networks of Internet-mediated prostitution , 2010, Proceedings of the National Academy of Sciences.

[20]  P. Schmid-Hempel,et al.  Social Immunity , 2007, Current Biology.

[21]  Petter Holme,et al.  Simulated Epidemics in an Empirical Spatiotemporal Network of 50,185 Sexual Contacts , 2010, PLoS Comput. Biol..

[22]  Ferenc Jordán,et al.  Infectious disease and group size: more than just a numbers game , 2015, Philosophical Transactions of the Royal Society B: Biological Sciences.

[23]  Nathalie Stroeymeyt,et al.  Organisational immunity in social insects. , 2014, Current opinion in insect science.

[24]  J. Traniello,et al.  Immunity in a Social Insect , 1999, Naturwissenschaften.

[25]  JOHN FIEBERG,et al.  QUANTIFYING HOME-RANGE OVERLAP: THE IMPORTANCE OF THE UTILIZATION DISTRIBUTION , 2005 .

[26]  Sebastian Bonhoeffer,et al.  Short-term activity cycles impede information transmission in ant colonies , 2017, PLoS Comput. Biol..

[27]  M E J Newman Assortative mixing in networks. , 2002, Physical review letters.

[28]  Nigel R. Franks,et al.  Task allocation in ant colonies within variable environments (a study of temporal polyethism: Experimental) , 1993 .

[29]  Shweta Bansal,et al.  Unraveling the disease consequences and mechanisms of modular structure in animal social networks , 2017, Proceedings of the National Academy of Sciences.

[30]  Scott Camazine,et al.  The role of colony organization on pathogen transmission in social insects. , 2002, Journal of theoretical biology.

[31]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[32]  V Latora,et al.  Efficient behavior of small-world networks. , 2001, Physical review letters.

[33]  J. Boomsma,et al.  Trade-offs in group living: transmission and disease resistance in leaf-cutting ants , 2002, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[34]  Diversity, prevalence and virulence of fungal entomopathogens in colonies of the ant Formica selysi , 2012, Insectes Sociaux.

[35]  Matt J Keeling,et al.  Modeling dynamic and network heterogeneities in the spread of sexually transmitted diseases , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[36]  P. E. Kopp,et al.  Superspreading and the effect of individual variation on disease emergence , 2005, Nature.

[37]  S. Xavier-Santos,et al.  Differentiation of the entomopathogenic fungus Metarhizium flavoviride (Hyphomycetes) , 1999 .

[38]  M. Bidochka,et al.  Diversity and abundance of entomopathogenic fungi at ant colonies. , 2018, Journal of invertebrate pathology.

[39]  Marcel Salathé,et al.  Dynamics and Control of Diseases in Networks with Community Structure , 2010, PLoS Comput. Biol..

[40]  Jeffrey M. Wooldridge,et al.  Solutions Manual and Supplementary Materials for Econometric Analysis of Cross Section and Panel Data , 2003 .

[41]  J. Witte The Ants , 2016 .

[42]  Simon Benhamou,et al.  Animal movements in heterogeneous landscapes: identifying profitable places and homogeneous movement bouts. , 2008, Ecology.

[43]  T. O. Richardson,et al.  Beyond contact-based transmission networks: the role of spatial coincidence , 2015, Journal of The Royal Society Interface.

[44]  Menna E. Jones,et al.  Contact networks in a wild Tasmanian devil (Sarcophilus harrisii) population: using social network analysis to reveal seasonal variability in social behaviour and its implications for transmission of devil facial tumour disease. , 2009, Ecology letters.

[45]  Damien R Farine,et al.  When to choose dynamic vs. static social network analysis. , 2018, The Journal of animal ecology.

[46]  J. Krause,et al.  Potential banana skins in animal social network analysis , 2009, Behavioral Ecology and Sociobiology.

[47]  Gillespie,et al.  Light and electron microscopy studies of the infection of the western flower thrips frankliniella occidentalis (Thysanoptera: thripidae) by the entomopathogenic fungus metarhizium anisopliae , 1999, Journal of invertebrate pathology.

[48]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[49]  Christopher D. Pull,et al.  Tolerating an infection: an indirect benefit of co-founding queen associations in the ant Lasius niger , 2013, Naturwissenschaften.

[50]  M. Chapuisat,et al.  Wood ants produce a potent antimicrobial agent by applying formic acid on tree‐collected resin , 2017, Ecology and evolution.

[51]  Dhruba Naug,et al.  Experimentally induced change in infectious period affects transmission dynamics in a social group , 2007, Proceedings of the Royal Society B: Biological Sciences.

[52]  Jari Saramäki,et al.  Temporal Networks , 2011, Encyclopedia of Social Network Analysis and Mining.

[53]  B. König,et al.  Infection-induced behavioural changes reduce connectivity and the potential for disease spread in wild mice contact networks , 2016, Scientific Reports.