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We're located in the Chemistry Building (3rd Floor), just across N. University Avenue from the Bell Tower (above) on the main campus at the University of Michigan, Ann Arbor.

 

News

Publications

  2021

• Huynh, A. and Wood, K.  Antibiotic Resistance:  Finding the Right Sequence of Drugs [Insight Article], eLife, doi: 10.7554/eLife.72562 (2021).

• Gjini, E. and Wood, K.  Price equation captures the role of drug interactions and collateral effects in the evolution of multidrug resistance, eLife, doi: 10.7554:e64851 (2021). 

       Part of eLife's Special Issue on Evolutionary Medicine.

• Sharma, A. and Wood, K.  Spatial segregation and cooperation in radially expanding microbial colonies under antibiotic stress, ISME, doi: 10.1038/s41396-021-00982-2 (2021).

• Wood, K.  Time-dependent drug sequences for slowing antibiotic resistance.  In Roadmap on biology in time varying environments (Murugan et al), Physical Biology (2021).

 2020 

• Maltas, J., McNally, D., and Wood, K.  Evolution in alternating environments with tunable inter-landscape correlations, Evolution, 75 (1), 10-24 (2020). 

• Hansen^**, E., Karslake^**, J., Woods, R.J., Read, A.F., and Wood, K.  Antibiotics can be used to contain drug-resistant bacteria by maintaining sufficiently large sensitive populations, PLOS Biology, 18 (5), e3000713 (2020).

• Hallinen, K., Guardiola-Flores, K. A., and Wood, K.  Fluorescent reporter plasmids for single-cell and bulk-level composition assays in E. faecalis, PLOS One, 15(5): e0232539 (2020).

• Hallinen^**, K., Karslake^**,J. , and Wood, K.  Delayed antibiotic exposure induces population collapse in enterococcal communities with drug-resistant subpopulations, eLife, doi: 10.7554/eLife.52813 (2020).  eLife Digest

• Dean, Z., Maltas, J., and Wood, K.  Antibiotic interactions shape short-term evolution of resistance in E. faecalis, PLOS Pathogens, 16(3): e1008278 (2020).

2019

• Maltas, J., Krasnick, B., and Wood, K.  Using selection by non-antibiotic stressors to sensitize bacteria to antibiotics, Molecular Biology and Evolution, doi:10.1093/molbev/msz303 (2019).

• Maltas, J., and Wood, K.  Pervasive and diverse collateral sensitivity profiles inform optimal strategies to limit antibiotic resistance, PLOS Biology 17(10), e300515, 2019.

• Wood, K.  Microbial Ecology:  Complex Bacterial Communities Reduce Selection for Antibiotic Resistance [Invited Dispatch], Current Biology, 29, R1143-1145, 2019.

 2018

• De Jong, M. G., and Wood, K.  Tuning spatial profiles of selection pressure to modulate the evolution of drug resistance, Physical Review Letters, 120 (23), 2018.  PDF

• Yu, W., Hallinen, K., and Wood, K., Interplay between antibiotic efficacy and drug-induced lysis underlies enhanced biofilm formation at subinhibitory drug concentrations, Antimicrobial Agents and Chemotherapy, 62 (1), 2018.

Pre-2018

• Karslake, J., Maltas, J., Brumm, P., and Wood, K., Population density modulates drug inhibition and gives rise to potential bistability of treatment outcomes for bacterial infections, PLOS Computational Biology 12 (10) (2016).

• Wood, K.  Pairwise interactions and the battle against combinatorics in multidrug therapies [Invited Commentary], P Natl Acad Sci USA (2016).

• Yu, W. and Wood, K., Synchronization and phase redistribution in self-replicating populations of coupled oscillators and excitable elements, Phys. Rev. E, 91, 062708 (2015).

 

Overview

Biological systems are often celebrated for their tremendous complexity.  For example, the dynamics of metabolic networks in bacteria, the interplay between predators and prey in a large ecosystems, and the spread of epidemics in human populations all depend on interactions between the thousands, millions, or even billions of individual “parts” that make up the system. Despite this complexity, however, the behavior of these systems is often the result of relatively simple emergent properties that are shared by a large number of statistically similar, but microscopically distinct, systems.  Motivated by emergent phenomena across physical and biological disciplines, our group applies systems level approaches to the study of living systems, where biologically-relevant dynamics—for example, the evolution of drug-resistance in a population of cancer cells—emerge from interactions and competition between a large number of individual components.  While we study a wide range of biological systems, we are especially interested in multi-drug resistance in bacteria and cancer cells.  Our goal is the development of quantitative tools to measure and predict how interactions between cells and interactions between drugs contribute to large scale behavior of the population as a whole.  Our research is highly multidisciplinary and combines theoretical tools from physics, engineering, applied math, and computer science with experimental approaches from molecular biology, genetics, microbiology, and cancer biology.

Topics of current interest include:

• Evolution of microbial drug resistance in spatially heterogeneous environments;
• Single-cell spatial architecture in cooperative biofilms;
• Effects of coupling between population density and fitness in microbial populations;
• The interplay between multi-drug interactions, drug cycling, and ecological dynamics in bacteria and cancer;
  
• The role of network structure and critical dynamics in determining the responses of large statistical mechanical systems, including those close to and far from equilibrium, to single and combined perturbations.
• Synchronization phenomena in self-replicating populations of coupled oscillators

Welcome to the Wood Lab at the University of Michigan!

Department of Biophysics and Department of Physics