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Remy Chait
Researcher at Harvard University
Publications - 20
Citations - 5693
Remy Chait is an academic researcher from Harvard University. The author has contributed to research in topics: Population & Antibiotic resistance. The author has an hindex of 17, co-authored 19 publications receiving 5077 citations. Previous affiliations of Remy Chait include Institute of Science and Technology Austria & University of Exeter.
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Nonoptimal Microbial Response to Antibiotics Underlies Suppressive Drug Interactions
TL;DR: Using GFP-tagged transcription reporters in Escherichia coli, it is found that ribosomal genes are not directly regulated by DNA stress, leading to an imbalance between cellular DNA and protein content, and a simple mathematical model explains the nonoptimal regulation in different nutrient environments.
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Drug interactions modulate the potential for evolution of resistance
TL;DR: Analysis of interactions between pairs of drugs affects the spontaneous emergence of resistance in the medically important pathogen Staphylococcus aureus reveals the central role of drug epistasis in the evolution of resistance and points to new strategies for combating the emergence of drug-resistant bacteria.
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Optimal Drug Synergy in Antimicrobial Treatments
TL;DR: It is found that synergy has two conflicting effects: it clears the infection faster and thereby decreases the time during which resistant mutants can arise, but increases the selective advantage of these mutants over wild-type cells.
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Building a morbidostat: an automated continuous-culture device for studying bacterial drug resistance under dynamically sustained drug inhibition
Erdal Toprak,Adrian Veres,Sadik Yildiz,Juan M. Pedraza,Remy Chait,Johan Paulsson,Roy Kishony +6 more
TL;DR: The morbidostat is used to follow the evolution of microbial drug resistance in real time and constantly measures the growth rates of evolving microbial populations and dynamically adjusts drug concentrations inside culture vials in order to maintain a constant drug-induced inhibition.
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Shaping bacterial population behavior through computer-interfaced control of individual cells.
Remy Chait,Jakob Ruess,Jakob Ruess,Jakob Ruess,Tobias Bergmiller,Gašper Tkačik,Călin C. Guet +6 more
TL;DR: An automated, programmable platform that combines image-based gene expression and growth measurements with on-line optogenetic expression control for hundreds of individual Escherichia coli cells over days, in a dynamically adjustable environment is presented.