Roy Kishony

Roy Kishony

Education/ Resume:

1989-1992            B.Sc, Mathematics and Physics, Talpiot Program of Excellency, Hebrew University (cum laude)
1992-1999            Ph.D., Direct Program, Physics (Profs. Shvarts& Kelson), Tel-Aviv University
1999-2001            Postdoc, Molecular Biology Department (Prof. S. Leibler), Princeton University
2001-2003            Postdoc, Center for Physics and Biology (Prof. S. Leibler), Rockefeller University

Research Summary:

From pathogen genomics to resistance-proof drug regimes
In the chemical warfare between bacteria and humans, the clinical use of antibiotics drives higher resistance levels by selecting for resistant bacteria. To make antibiotic treatment resilient to the evolution of resistance, one has to understand the ways in which bacteria evolve and become resistant, and identify the genomic determinants which potentiate them.

Our long term goal is to help design single-drug and multi-drug regimes that better prevent the emergence of resistance. In the lab and in the clinic, we follow bacteria as they are becoming more resistant, identifying the underlying mutations which enable these phenotypes and explore their dynamics on different genetic backgrounds and in different environments. In the future, these insights will allow genome-based “anticipatory” diagnostics of microbial infections that can predict future evolution and help prescribe more resilient antimicrobial treatments.

From big-data and machine-learning to personalized antibiotic treatment
Antibiotic drugs save human lives threatened by infections, but their effectiveness is hindered by antibiotic resistance. In the clinic, physicians face the challenge of prescribing the most effective antibiotic drug under conditions of uncertainty. Unique availability of millions of electronic health records and pathogen genomes, now allows us to develop a new kind of machine learning-based diagnostics algorithms that predict the current and future infection-specific profile of resistance,

and suggest an optimized personally-tailored treatment. We are currently pursuing the development of more powerful and comprehensible algorithms which will provide the basis for advanced data-driven decision support systems which will suggest optimized treatment in real-time. These future systems have the potential to improve individual patient treatment outcomes and overall patient health, while at the same time helping in the global effort to impede the antibiotic resistance epidemic.

From species evolution and species interactions to whole community dynamics and stability
In natural ecosystems bacteria grow, migrate and compete over nutrients in dense and diverse communities. In such communities, antibiotic production and antibiotic resistance genes evolve in a continuous arms race. Our goal is to identify the principles governing the evolution, maintenance and refinement of these antibiotic-based interactions.

Allowing bacteria to co-evolve in laboratory settings we follow the role of evolution in shaping such multi-bacterial communities. Encapsulating competing species in artificial microenvironments we challenge bacteria to enhance toxicity and explore the evolutionary pathways leading on one hand to increased antibiotic resistance and on the other hand to improved antibiotic production.


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Selected Awards:

2022       Rappaport Prize for an Established Researcher
2021       Landau Award in Bioinformatics
2020       Diane Sherman Prize for Medical Innovations for a Better World
2018       Member, European Academy of Microbiology (EAM)
2017       Member, European Molecular Biology Organization (EMBO)
2017       Member, 8400 – The Health Network
2016       Member, Israel Young Academy
2016       Michael Bruno Memorial Award
2013       Sanofi – Institut Pasteur Award
2011       Honorary Master in Art and Sciences, Harvard University
2009       Outstanding Achievement in Biomedical Science Award, Genzyme

Key Publications:

M. Stracy, O. Snitser, I. Yelin, Y. Amer, M. Parizade, G. Rimler, T. Wolf, R. Katz, E. Herzel, G. Koren, J. Kuint, B. Foxman, G. Chodick, V. Shalev, R. Kishony “Minimizing treatment-induced emergence of antibiotic resistance in bacterial infections”. Science (2022).

I.Yelin, O. Snitser, G. Novich, R. Katz, O. Tal, M. Parizade, G. Chodick, G. Koren, V. Shalev, R. Kishony, “Personal clinical history predicts antibiotic resistance in urinary tract infections”, Nature Medicine (2019).

D.Russ & R. Kishony, “Additivity of inhibitory effects in multi-drug combinations”, Nature Microbiology (2018).

M.Baym, T. D. Lieberman, E. D. Kelsic, R. Chait, R. Gross, I. Yelin, R. Kishony, “Spatiotemporal microbial evolution on antibiotic landscapes”, Science 353, 1147 (2016).

T.D. Lieberman, K. B. Flett, I. Yelin, T. R. Martin, A. J. McAdam*, G. P. Priebe*, R. Kishony*, “Genetic variation of a bacterial pathogen within individuals with cystic fibrosis provides a record of selective pressures”, Nature Genetics 46, 82 (2014).

E.Toprak*, A. Veres*, J-B Michel, R. Chait, D. L Hartl, R. Kishony, “Evolutionary paths to antibiotic resistance under dynamically sustained drug selection”, Nature Genetics 44 (1), 101 (2012).

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Recent Publications:
  • M. Levine-Tiefenbrun, I. Yelin, H. Alapi, E. Herzel, J. Kuint, G. Chodick, S. Gazit, T. Patalon†, R. Kishony† “Waning of SARS-CoV-2 booster viral-load reduction effectiveness”. Nature Communications (2022).
  • M.S. Datta*, I. Yelin*, O. Hochwald, I. Kassis, L. Borenstein-Levin, A. Kugelman & R. Kishony. “Rapid methicillin resistance diversification in Staphylococcus epidermidis colonizing human neonates”. Nature Communications (2021).
  •  O. Milman*, I. Yelin*, N. Aharony, R. Katz, E. Herzel, A. Ben-Tov, J. Kuint, S. Gazit, G. Chodick, T. Patalon†, R. Kishony†. “SARS-CoV-2 infection risk among unvaccinated is negatively associated with community-level vaccination rates”. Nature Medicine (2021).
  • M. Levine-Tiefenbrun*, I. Yelin*, R. Katz, E. Herzel, Z. Golan, L. Schreiber, T. Wolf, V. Nadler, A. Ben-Tov, J. Kuint, S. Gazit, T. Patalon, G. Chodick, R. Kishony. “Initial report of decreased SARS-CoV-2 viral load after inoculation with the BNT162b2 vaccine”. Nature Medicine (2021).
  • O. Snitser, D. Russ, L.K Stone, K.K Wang, H. Sharir, N. Kozer, G. Cohen, H.M Barr, R. Kishony, “Ubiquitous selection for mecA in community-associated MRSA across diverse chemical environments” Nature Communications (2020).
  • I. Yelin*, N. Aharony*, E. Shaer-Tamar*, A. Argoetti*, E. Messer, D. Berenbaum, E. Shafran, A. Kuzli, N. Gandali, O. Shkedi, T. Hashimshony, Y. Mandel-Gutfreund, M. Halberthal†, Y. Geffen†, M. Szwarcwort-Cohen†, R. Kishony†. “Evaluation of COVID-19 RT-qPCR test in multi-sample pools”. Clinical Infectious Diseases (2020).
  • D. Russ, F. Glaser, E. Shaer-Tamar, I. Yelin, M. Baym, E.D. Kelsic, C. Zampaloni, A. Haldimann, R. Kishony. “Escape mutations circumvent a tradeoff between resistance to a beta-lactam and a beta-lactamase inhibitor”. Nature Communications (2020), 11(1), pp.1-9.
  • I. Yelin*, K.B. Flett*, C. Merakou*, P. Mehrotra, J. Stam, E. Snesrud, M. Hikle, E. Lesho, P. McGann, A.J. McAdam, T.J. Sandora†, R. Kishony†, G.P. Priebe† .”Genomic and epidemiological evidence of bacterial transmission from probiotic capsule to blood in ICU patients”. Nature Medicine 25 (2019), 1728–1732.
  • A. C. Palmer, R. Chait, R. Kishony, “Non-optimal gene expression creates latent potential for antibiotic resistance”, Molecular Biology and Evolution (2018).
  • D. Schultz, A.C Palmer, R. Kishony, “Regulatory dynamics determine cell fate following abrupt antibiotic exposure”, Cell Systems (2017).
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