TY - JOUR
T1 - Fighting microbial pathogens by integrating host ecosystem interactions and evolution
AU - Burmeister, Alita R.
AU - Hansen, Elsa
AU - Cunningham, Jessica J.
AU - Rego, E. Hesper
AU - Turner, Paul E.
AU - Weitz, Joshua S.
AU - Hochberg, Michael E.
N1 - Funding Information:
Special thanks to Michael Donoghue and the Yale Institute for Biospheric Studies for hosting the workshop “Novel Approaches to Combating Therapeutic Resistance.” We thank Jeffrey Townsend, Troy Day and Jessica Metcalf for discussions, and Mike Blazanin and Silvie Huijben and an anonymous reviewer for useful comments on this manuscript. BioRender.com was used to generate Figures 1 and 2 . ARB and PET: Our work was supported by an NIH Grant #R21AI144345 from the National Institute of Allergy and Infectious Diseases. PET: Generous support from the Yale Institute for Biospheric Studies. EH: Eberly Family Trust. EHR is supported by the Pew Biomedical Research Program and the Searle Scholars Program. JJC: James S. McDonnell Foundation grant, Cancer therapy: Perturbing a complex adaptive system, a V Foundation grant, NIH/National Cancer Institute (NCI) R01CA170595, Application of Evolutionary Principles to Maintain Cancer Control (PQ21), and NIH/NCI U54CA143970‐05 [Physical Science Oncology Network (PSON)] Cancer as a complex adaptive system. JSW acknowledges support from NIH 1R01AI46592‐01, NSF 1806606, and ARO W911NF1910384. MEH thanks ITMO Cancer AVIESAN (HetColi 226132), the McDonnell Foundation (Studying Complex Systems Research Award No. 220020294), and the Institut National du Cancer (2014‐1‐PL‐BIO‐12‐IGR‐1) for funding.
Publisher Copyright:
© 2020 Wiley Periodicals LLC
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - Successful therapies to combat microbial diseases and cancers require incorporating ecological and evolutionary principles. Drawing upon the fields of ecology and evolutionary biology, we present a systems-based approach in which host and disease-causing factors are considered as part of a complex network of interactions, analogous to studies of “classical” ecosystems. Centering this approach around empirical examples of disease treatment, we present evidence that successful therapies invariably engage multiple interactions with other components of the host ecosystem. Many of these factors interact nonlinearly to yield synergistic benefits and curative outcomes. We argue that these synergies and nonlinear feedbacks must be leveraged to improve the study of pathogenesis in situ and to develop more effective therapies. An eco-evolutionary systems perspective has surprising and important consequences, and we use it to articulate areas of high research priority for improving treatment strategies.
AB - Successful therapies to combat microbial diseases and cancers require incorporating ecological and evolutionary principles. Drawing upon the fields of ecology and evolutionary biology, we present a systems-based approach in which host and disease-causing factors are considered as part of a complex network of interactions, analogous to studies of “classical” ecosystems. Centering this approach around empirical examples of disease treatment, we present evidence that successful therapies invariably engage multiple interactions with other components of the host ecosystem. Many of these factors interact nonlinearly to yield synergistic benefits and curative outcomes. We argue that these synergies and nonlinear feedbacks must be leveraged to improve the study of pathogenesis in situ and to develop more effective therapies. An eco-evolutionary systems perspective has surprising and important consequences, and we use it to articulate areas of high research priority for improving treatment strategies.
UR - http://www.scopus.com/inward/record.url?scp=85098499500&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85098499500&partnerID=8YFLogxK
U2 - 10.1002/bies.202000272
DO - 10.1002/bies.202000272
M3 - Article
C2 - 33377530
AN - SCOPUS:85098499500
SN - 0265-9247
VL - 43
JO - BioEssays
JF - BioEssays
IS - 3
M1 - 2000272
ER -