Edo Kussell

Professor of Biology and Physics

Education

Ph.D. (Physics), Harvard University

Areas of Research/Interest

Computational biology, evolution, and biological physics

Research

Classical studies of molecular biology revealed how cells sense their environment and respond to change, establishing the centrality of gene regulation in cellular physiology. Numerous mechanisms in bacteria, however, function in a largely deregulated way, generating a diversity of responses across the population, without necessarily sensing the environment. The existence of such stochastic mechanisms raises several (increasingly difficult) questions: (1) How do microorganisms employ stochasticity to their advantage? (2) Can we distinguish such adaptive stochasticity from useless noise that is simply too costly for cells to avoid? (3) How, and under what circumstances, do sensing mechanisms evolve? My research employs theoretical and computational modeling of bacteria populations in fluctuating environments, and comparative genomics of experimentally-characterized stochastic switches.

Closely related topics of research include the evolution of mutation rates, mutator phenotypes, and mutational hotspots in genomes. My other interests include protein folding and protein evolution.

Biosketch

I received my Ph.D in Biophysics from Harvard University, where I worked with Eugene Shakhnovich on physical aspects of protein folding, including relaxation dynamics and packing of protein sidechains, high-resolution Monte Carlo simulation of folding, and theory related to protein evolution. I went on to do post-doctoral work with Stanislas Leibler at The Rockefeller University where, starting with simple models of antibiotic persistence in E. coli, we worked towards understanding in some generality the evolutionary advantage of stochastic phenotype switches in microorganisms. We eventually found that these mechanisms are intimately connected with information acquisition in a general sense, and that in certain cases the evolutionary advantage of phenotype switching can be expressed in purely information theoretic terms. I joined the NYU faculty in the Department of Biology in September 2006, where I am working on theory and modeling of evolution in microorganisms.

Teaching

Biol-GA.1131 (cross-listed as MATH-GA.2852/PHYS-GA.2081) Biophysical Modeling of Cells and Populations

Publications

Date of these PubMed search results: March 24 2020
Get the current Pubmed search results

  1. Inferring bacterial recombination rates from large-scale sequencing datasets.
    Nat Methods (2019 Feb) PMID: 30664775
    Lin M, Kussell E
  2. The impact of bottlenecks on microbial survival, adaptation, and phenotypic switching in host-pathogen interactions.
    Evolution (2017 Dec) PMC5722657 free full-text archive
    Moxon R, Kussell E
  3. Inferring fitness landscapes and selection on phenotypic states from single-cell genealogical data.
    PLoS Genet (2017 Mar) PMC5360348 free full-text archive
    Nozoe T, Kussell E, Wakamoto Y
  4. Correlated Mutations and Homologous Recombination Within Bacterial Populations.
    Genetics (2017 Feb) PMC5289858 free full-text archive
    Lin M, Kussell E
  5. Evolutionary Phase Transitions in Random Environments.
    Phys Rev Lett (2016 Jul 15) PMC5697730 free full-text archive
    Skanata A, Kussell E
  6. Complex Interplay of Physiology and Selection in the Emergence of Antibiotic Resistance.
    Curr Biol (2016 Jun 6) PMC4899102 free full-text archive
    Lin WH, Kussell E
  7. Noise-driven growth rate gain in clonal cellular populations.
    Proc Natl Acad Sci U S A (2016 Mar 22) PMC4812751 free full-text archive
    Hashimoto M, Nozoe T, Nakaoka H, Okura R, Akiyoshi S, Kaneko K, Kussell E, Wakamoto Y
  8. Bacterial Autoimmunity Due to a Restriction-Modification System.
    Curr Biol (2016 Feb 8) PMID: 26804559
    Pleska M, Qian L, Okura R, Bergmiller T, Wakamoto Y, Kussell E, Guet CC
  9. Quantifying selective pressures driving bacterial evolution using lineage analysis.
    Phys Rev X (2015 Jan-Mar) PMC4511495 free full-text archive
    Lambert G, Kussell E
  10. Populations adapt to fluctuating selection using derived and ancestral allelic diversity.
    Evolution (2015 Jun) PMC4478211 free full-text archive
    Lin WH, Rocco MJ, Bertozzi‑Villa A, Kussell E
  11. Non-equilibrium physics and evolution--adaptation, extinction, and ecology: a key issues review.
    Rep Prog Phys (2014 Oct) PMID: 25303141
    Kussell E, Vucelja M
  12. Memory and fitness optimization of bacteria under fluctuating environments.
    PLoS Genet (2014 Sep) PMC4177670 free full-text archive
    Lambert G, Kussell E
  13. Evolution in microbes.
    Annu Rev Biophys (2013) PMID: 23654305
    Kussell E
  14. Evolutionary dynamics of restriction site avoidance.
    Phys Rev Lett (2012 Apr 13) PMID: 22587291
    Qian L, Kussell E
  15. Stochastic de-repression of Rhodopsins in single photoreceptors of the fly retina.
    PLoS Comput Biol (2012 Feb) PMC3271025 free full-text archive
    Sood P, Johnston RJ Jr, Kussell E
  16. Optimal lineage principle for age-structured populations.
    Evolution (2012 Jan) PMID: 22220869
    Wakamoto Y, Grosberg AY, Kussell E
  17. Evolutionary pressures on simple sequence repeats in prokaryotic coding regions.
    Nucleic Acids Res (2012 Mar) PMC3315296 free full-text archive
    Lin WH, Kussell E
  18. Measuring cell identity in noisy biological systems.
    Nucleic Acids Res (2011 Nov) PMC3241637 free full-text archive
    Birnbaum KD, Kussell E
  19. Interlocked feedforward loops control cell-type-specific Rhodopsin expression in the Drosophila eye.
    Cell (2011 Jun 10) PMC3117217 free full-text archive
    Johnston RJ Jr, Otake Y, Sood P, Vogt N, Behnia R, Vasiliauskas D, McDonald E, Xie B, Koenig S, Wolf R, Cook T, Gebelein B, Kussell E, Nakagoshi H, Desplan C
  20. Individual histories and selection in heterogeneous populations.
    Proc Natl Acad Sci U S A (2010 Jul 20) PMC2919897 free full-text archive
    Leibler S, Kussell E
  21. Polymer-population mapping and localization in the space of phenotypes.
    Phys Rev Lett (2006 Aug 11) PMID: 17026205
    Kussell E, Leibler S, Grosberg A
  22. Phenotypic diversity, population growth, and information in fluctuating environments.
    Science (2005 Sep 23) PMID: 16123265
    Kussell E, Leibler S
  23. The designability hypothesis and protein evolution.
    Protein Pept Lett (2005 Feb) PMID: 15723636
    Kussell E
  24. Bacterial persistence: a model of survival in changing environments.
    Genetics (2005 Apr) PMC1449587 free full-text archive
    Kussell E, Kishony R, Balaban NQ, Leibler S
  25. Side-chain dynamics and protein folding.
    Proteins (2003 Aug 1) PMID: 12833553
    Kussell E, Shimada J, Shakhnovich EI
  26. Glassy dynamics of side-chain ordering in a simple model of protein folding.
    Phys Rev Lett (2002 Oct 14) PMID: 12398757
    Kussell E, Shakhnovich EI
  27. A structure-based method for derivation of all-atom potentials for protein folding.
    Proc Natl Acad Sci U S A (2002 Apr 16) PMC122771 free full-text archive
    Kussell E, Shimada J, Shakhnovich EI
  28. Excluded volume in protein side-chain packing.
    J Mol Biol (2001 Aug 3) PMID: 11469867
    Kussell E, Shimada J, Shakhnovich EI
  29. The folding thermodynamics and kinetics of crambin using an all-atom Monte Carlo simulation.
    J Mol Biol (2001 Apr 20) PMID: 11302709
    Shimada J, Kussell EL, Shakhnovich EI
  30. Recovery of protein structure from contact maps.
    Fold Des (1997) PMID: 9377713
    Vendruscolo M, Kussell E, Domany E