---
_id: '10939'
abstract:
- lang: eng
  text: Understanding and characterising biochemical processes inside single cells
    requires experimental platforms that allow one to perturb and observe the dynamics
    of such processes as well as computational methods to build and parameterise models
    from the collected data. Recent progress with experimental platforms and optogenetics
    has made it possible to expose each cell in an experiment to an individualised
    input and automatically record cellular responses over days with fine time resolution.
    However, methods to infer parameters of stochastic kinetic models from single-cell
    longitudinal data have generally been developed under the assumption that experimental
    data is sparse and that responses of cells to at most a few different input perturbations
    can be observed. Here, we investigate and compare different approaches for calculating
    parameter likelihoods of single-cell longitudinal data based on approximations
    of the chemical master equation (CME) with a particular focus on coupling the
    linear noise approximation (LNA) or moment closure methods to a Kalman filter.
    We show that, as long as cells are measured sufficiently frequently, coupling
    the LNA to a Kalman filter allows one to accurately approximate likelihoods and
    to infer model parameters from data even in cases where the LNA provides poor
    approximations of the CME. Furthermore, the computational cost of filtering-based
    iterative likelihood evaluation scales advantageously in the number of measurement
    times and different input perturbations and is thus ideally suited for data obtained
    from modern experimental platforms. To demonstrate the practical usefulness of
    these results, we perform an experiment in which single cells, equipped with an
    optogenetic gene expression system, are exposed to various different light-input
    sequences and measured at several hundred time points and use parameter inference
    based on iterative likelihood evaluation to parameterise a stochastic model of
    the system.
acknowledgement: We thank Virgile Andreani for useful discussions about the model
  and parameter inference. We thank Johan Paulsson and Jeffrey J Tabor for kind gifts
  of plasmids. R was supported by the ANR grant CyberCircuits (ANR-18-CE91-0002).
  The funders had no role in study design, data collection and analysis, decision
  to publish, or preparation of the manuscript.
article_number: e1009950
article_processing_charge: No
article_type: original
author:
- first_name: Anđela
  full_name: Davidović, Anđela
  last_name: Davidović
- first_name: Remy P
  full_name: Chait, Remy P
  id: 3464AE84-F248-11E8-B48F-1D18A9856A87
  last_name: Chait
  orcid: 0000-0003-0876-3187
- first_name: Gregory
  full_name: Batt, Gregory
  last_name: Batt
- first_name: Jakob
  full_name: Ruess, Jakob
  id: 4A245D00-F248-11E8-B48F-1D18A9856A87
  last_name: Ruess
  orcid: 0000-0003-1615-3282
citation:
  ama: Davidović A, Chait RP, Batt G, Ruess J. Parameter inference for stochastic
    biochemical models from perturbation experiments parallelised at the single cell
    level. <i>PLoS Computational Biology</i>. 2022;18(3). doi:<a href="https://doi.org/10.1371/journal.pcbi.1009950">10.1371/journal.pcbi.1009950</a>
  apa: Davidović, A., Chait, R. P., Batt, G., &#38; Ruess, J. (2022). Parameter inference
    for stochastic biochemical models from perturbation experiments parallelised at
    the single cell level. <i>PLoS Computational Biology</i>. Public Library of Science.
    <a href="https://doi.org/10.1371/journal.pcbi.1009950">https://doi.org/10.1371/journal.pcbi.1009950</a>
  chicago: Davidović, Anđela, Remy P Chait, Gregory Batt, and Jakob Ruess. “Parameter
    Inference for Stochastic Biochemical Models from Perturbation Experiments Parallelised
    at the Single Cell Level.” <i>PLoS Computational Biology</i>. Public Library of
    Science, 2022. <a href="https://doi.org/10.1371/journal.pcbi.1009950">https://doi.org/10.1371/journal.pcbi.1009950</a>.
  ieee: A. Davidović, R. P. Chait, G. Batt, and J. Ruess, “Parameter inference for
    stochastic biochemical models from perturbation experiments parallelised at the
    single cell level,” <i>PLoS Computational Biology</i>, vol. 18, no. 3. Public
    Library of Science, 2022.
  ista: Davidović A, Chait RP, Batt G, Ruess J. 2022. Parameter inference for stochastic
    biochemical models from perturbation experiments parallelised at the single cell
    level. PLoS Computational Biology. 18(3), e1009950.
  mla: Davidović, Anđela, et al. “Parameter Inference for Stochastic Biochemical Models
    from Perturbation Experiments Parallelised at the Single Cell Level.” <i>PLoS
    Computational Biology</i>, vol. 18, no. 3, e1009950, Public Library of Science,
    2022, doi:<a href="https://doi.org/10.1371/journal.pcbi.1009950">10.1371/journal.pcbi.1009950</a>.
  short: A. Davidović, R.P. Chait, G. Batt, J. Ruess, PLoS Computational Biology 18
    (2022).
date_created: 2022-04-03T22:01:42Z
date_published: 2022-03-18T00:00:00Z
date_updated: 2022-04-04T10:21:53Z
day: '18'
ddc:
- '570'
- '000'
department:
- _id: CaGu
doi: 10.1371/journal.pcbi.1009950
file:
- access_level: open_access
  checksum: 458ef542761fb714ced214f240daf6b2
  content_type: application/pdf
  creator: dernst
  date_created: 2022-04-04T10:14:39Z
  date_updated: 2022-04-04T10:14:39Z
  file_id: '10947'
  file_name: 2022_PLoSCompBio_Davidovic.pdf
  file_size: 2958642
  relation: main_file
  success: 1
file_date_updated: 2022-04-04T10:14:39Z
has_accepted_license: '1'
intvolume: '        18'
issue: '3'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
publication: PLoS Computational Biology
publication_identifier:
  eissn:
  - 1553-7358
  issn:
  - 1553-734X
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
  link:
  - relation: software
    url: https://gitlab.pasteur.fr/adavidov/inferencelnakf
scopus_import: '1'
status: public
title: Parameter inference for stochastic biochemical models from perturbation experiments
  parallelised at the single cell level
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 18
year: '2022'
...
---
_id: '9822'
abstract:
- lang: eng
  text: Attachment of adhesive molecules on cell culture surfaces to restrict cell
    adhesion to defined areas and shapes has been vital for the progress of in vitro
    research. In currently existing patterning methods, a combination of pattern properties
    such as stability, precision, specificity, high-throughput outcome, and spatiotemporal
    control is highly desirable but challenging to achieve. Here, we introduce a versatile
    and high-throughput covalent photoimmobilization technique, comprising a light-dose-dependent
    patterning step and a subsequent functionalization of the pattern via click chemistry.
    This two-step process is feasible on arbitrary surfaces and allows for generation
    of sustainable patterns and gradients. The method is validated in different biological
    systems by patterning adhesive ligands on cell-repellent surfaces, thereby constraining
    the growth and migration of cells to the designated areas. We then implement a
    sequential photopatterning approach by adding a second switchable patterning step,
    allowing for spatiotemporal control over two distinct surface patterns. As a proof
    of concept, we reconstruct the dynamics of the tip/stalk cell switch during angiogenesis.
    Our results show that the spatiotemporal control provided by our “sequential photopatterning”
    system is essential for mimicking dynamic biological processes and that our innovative
    approach has great potential for further applications in cell science.
acknowledgement: We would like to thank Charlott Leu for the production of our chromium
  wafers, Louise Ritter for her contribution of the IF stainings in Figure 4, Shokoufeh
  Teymouri for her help with the Bioinert coated slides, and finally Prof. Dr. Joachim
  Rädler for his valuable scientific guidance.
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Themistoklis
  full_name: Zisis, Themistoklis
  last_name: Zisis
- first_name: Jan
  full_name: Schwarz, Jan
  id: 346C1EC6-F248-11E8-B48F-1D18A9856A87
  last_name: Schwarz
- first_name: Miriam
  full_name: Balles, Miriam
  last_name: Balles
- first_name: Maibritt
  full_name: Kretschmer, Maibritt
  last_name: Kretschmer
- first_name: Maria
  full_name: Nemethova, Maria
  id: 34E27F1C-F248-11E8-B48F-1D18A9856A87
  last_name: Nemethova
- first_name: Remy P
  full_name: Chait, Remy P
  id: 3464AE84-F248-11E8-B48F-1D18A9856A87
  last_name: Chait
  orcid: 0000-0003-0876-3187
- first_name: Robert
  full_name: Hauschild, Robert
  id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87
  last_name: Hauschild
  orcid: 0000-0001-9843-3522
- first_name: Janina
  full_name: Lange, Janina
  last_name: Lange
- first_name: Calin C
  full_name: Guet, Calin C
  id: 47F8433E-F248-11E8-B48F-1D18A9856A87
  last_name: Guet
  orcid: 0000-0001-6220-2052
- first_name: Michael K
  full_name: Sixt, Michael K
  id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87
  last_name: Sixt
  orcid: 0000-0002-4561-241X
- first_name: Stefan
  full_name: Zahler, Stefan
  last_name: Zahler
citation:
  ama: Zisis T, Schwarz J, Balles M, et al. Sequential and switchable patterning for
    studying cellular processes under spatiotemporal control. <i>ACS Applied Materials
    and Interfaces</i>. 2021;13(30):35545–35560. doi:<a href="https://doi.org/10.1021/acsami.1c09850">10.1021/acsami.1c09850</a>
  apa: Zisis, T., Schwarz, J., Balles, M., Kretschmer, M., Nemethova, M., Chait, R.
    P., … Zahler, S. (2021). Sequential and switchable patterning for studying cellular
    processes under spatiotemporal control. <i>ACS Applied Materials and Interfaces</i>.
    American Chemical Society. <a href="https://doi.org/10.1021/acsami.1c09850">https://doi.org/10.1021/acsami.1c09850</a>
  chicago: Zisis, Themistoklis, Jan Schwarz, Miriam Balles, Maibritt Kretschmer, Maria
    Nemethova, Remy P Chait, Robert Hauschild, et al. “Sequential and Switchable Patterning
    for Studying Cellular Processes under Spatiotemporal Control.” <i>ACS Applied
    Materials and Interfaces</i>. American Chemical Society, 2021. <a href="https://doi.org/10.1021/acsami.1c09850">https://doi.org/10.1021/acsami.1c09850</a>.
  ieee: T. Zisis <i>et al.</i>, “Sequential and switchable patterning for studying
    cellular processes under spatiotemporal control,” <i>ACS Applied Materials and
    Interfaces</i>, vol. 13, no. 30. American Chemical Society, pp. 35545–35560, 2021.
  ista: Zisis T, Schwarz J, Balles M, Kretschmer M, Nemethova M, Chait RP, Hauschild
    R, Lange J, Guet CC, Sixt MK, Zahler S. 2021. Sequential and switchable patterning
    for studying cellular processes under spatiotemporal control. ACS Applied Materials
    and Interfaces. 13(30), 35545–35560.
  mla: Zisis, Themistoklis, et al. “Sequential and Switchable Patterning for Studying
    Cellular Processes under Spatiotemporal Control.” <i>ACS Applied Materials and
    Interfaces</i>, vol. 13, no. 30, American Chemical Society, 2021, pp. 35545–35560,
    doi:<a href="https://doi.org/10.1021/acsami.1c09850">10.1021/acsami.1c09850</a>.
  short: T. Zisis, J. Schwarz, M. Balles, M. Kretschmer, M. Nemethova, R.P. Chait,
    R. Hauschild, J. Lange, C.C. Guet, M.K. Sixt, S. Zahler, ACS Applied Materials
    and Interfaces 13 (2021) 35545–35560.
date_created: 2021-08-08T22:01:28Z
date_published: 2021-08-04T00:00:00Z
date_updated: 2023-08-10T14:22:48Z
day: '04'
ddc:
- '620'
- '570'
department:
- _id: MiSi
- _id: GaTk
- _id: Bio
- _id: CaGu
doi: 10.1021/acsami.1c09850
ec_funded: 1
external_id:
  isi:
  - '000683741400026'
  pmid:
  - '34283577'
file:
- access_level: open_access
  checksum: b043a91d9f9200e467b970b692687ed3
  content_type: application/pdf
  creator: asandaue
  date_created: 2021-08-09T09:44:03Z
  date_updated: 2021-08-09T09:44:03Z
  file_id: '9833'
  file_name: 2021_ACSAppliedMaterialsAndInterfaces_Zisis.pdf
  file_size: 7123293
  relation: main_file
  success: 1
file_date_updated: 2021-08-09T09:44:03Z
has_accepted_license: '1'
intvolume: '        13'
isi: 1
issue: '30'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 35545–35560
pmid: 1
project:
- _id: 25FE9508-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '724373'
  name: Cellular navigation along spatial gradients
publication: ACS Applied Materials and Interfaces
publication_identifier:
  eissn:
  - '19448252'
  issn:
  - '19448244'
publication_status: published
publisher: American Chemical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Sequential and switchable patterning for studying cellular processes under
  spatiotemporal control
tmp:
  image: /images/cc_by_nc_nd.png
  legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
  name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
    (CC BY-NC-ND 4.0)
  short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 13
year: '2021'
...
---
_id: '19'
abstract:
- lang: eng
  text: Bacteria regulate genes to survive antibiotic stress, but regulation can be
    far from perfect. When regulation is not optimal, mutations that change gene expression
    can contribute to antibiotic resistance. It is not systematically understood to
    what extent natural gene regulation is or is not optimal for distinct antibiotics,
    and how changes in expression of specific genes quantitatively affect antibiotic
    resistance. Here we discover a simple quantitative relation between fitness, gene
    expression, and antibiotic potency, which rationalizes our observation that a
    multitude of genes and even innate antibiotic defense mechanisms have expression
    that is critically nonoptimal under antibiotic treatment. First, we developed
    a pooled-strain drug-diffusion assay and screened Escherichia coli overexpression
    and knockout libraries, finding that resistance to a range of 31 antibiotics could
    result from changing expression of a large and functionally diverse set of genes,
    in a primarily but not exclusively drug-specific manner. Second, by synthetically
    controlling the expression of single-drug and multidrug resistance genes, we observed
    that their fitness-expression functions changed dramatically under antibiotic
    treatment in accordance with a log-sensitivity relation. Thus, because many genes
    are nonoptimally expressed under antibiotic treatment, many regulatory mutations
    can contribute to resistance by altering expression and by activating latent defenses.
article_processing_charge: No
article_type: original
author:
- first_name: Adam
  full_name: Palmer, Adam
  last_name: Palmer
- first_name: Remy P
  full_name: Chait, Remy P
  id: 3464AE84-F248-11E8-B48F-1D18A9856A87
  last_name: Chait
  orcid: 0000-0003-0876-3187
- first_name: Roy
  full_name: Kishony, Roy
  last_name: Kishony
citation:
  ama: Palmer A, Chait RP, Kishony R. Nonoptimal gene expression creates latent potential
    for antibiotic resistance. <i>Molecular Biology and Evolution</i>. 2018;35(11):2669-2684.
    doi:<a href="https://doi.org/10.1093/molbev/msy163">10.1093/molbev/msy163</a>
  apa: Palmer, A., Chait, R. P., &#38; Kishony, R. (2018). Nonoptimal gene expression
    creates latent potential for antibiotic resistance. <i>Molecular Biology and Evolution</i>.
    Oxford University Press. <a href="https://doi.org/10.1093/molbev/msy163">https://doi.org/10.1093/molbev/msy163</a>
  chicago: Palmer, Adam, Remy P Chait, and Roy Kishony. “Nonoptimal Gene Expression
    Creates Latent Potential for Antibiotic Resistance.” <i>Molecular Biology and
    Evolution</i>. Oxford University Press, 2018. <a href="https://doi.org/10.1093/molbev/msy163">https://doi.org/10.1093/molbev/msy163</a>.
  ieee: A. Palmer, R. P. Chait, and R. Kishony, “Nonoptimal gene expression creates
    latent potential for antibiotic resistance,” <i>Molecular Biology and Evolution</i>,
    vol. 35, no. 11. Oxford University Press, pp. 2669–2684, 2018.
  ista: Palmer A, Chait RP, Kishony R. 2018. Nonoptimal gene expression creates latent
    potential for antibiotic resistance. Molecular Biology and Evolution. 35(11),
    2669–2684.
  mla: Palmer, Adam, et al. “Nonoptimal Gene Expression Creates Latent Potential for
    Antibiotic Resistance.” <i>Molecular Biology and Evolution</i>, vol. 35, no. 11,
    Oxford University Press, 2018, pp. 2669–84, doi:<a href="https://doi.org/10.1093/molbev/msy163">10.1093/molbev/msy163</a>.
  short: A. Palmer, R.P. Chait, R. Kishony, Molecular Biology and Evolution 35 (2018)
    2669–2684.
date_created: 2018-12-11T11:44:11Z
date_published: 2018-08-28T00:00:00Z
date_updated: 2023-10-17T11:51:06Z
day: '28'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1093/molbev/msy163
external_id:
  isi:
  - '000452567200006'
  pmid:
  - '30169679'
intvolume: '        35'
isi: 1
issue: '11'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.ncbi.nlm.nih.gov/pubmed/30169679
month: '08'
oa: 1
oa_version: Submitted Version
page: 2669 - 2684
pmid: 1
publication: Molecular Biology and Evolution
publication_identifier:
  issn:
  - 0737-4038
publication_status: published
publisher: Oxford University Press
publist_id: '8036'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Nonoptimal gene expression creates latent potential for antibiotic resistance
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2018'
...
---
_id: '613'
abstract:
- lang: eng
  text: 'Bacteria in groups vary individually, and interact with other bacteria and
    the environment to produce population-level patterns of gene expression. Investigating
    such behavior in detail requires measuring and controlling populations at the
    single-cell level alongside precisely specified interactions and environmental
    characteristics. Here we present 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. This integrated platform broadly enables experiments that
    bridge individual and population behaviors. We demonstrate: (i) population structuring
    by independent closed-loop control of gene expression in many individual cells,
    (ii) cell-cell variation control during antibiotic perturbation, (iii) hybrid
    bio-digital circuits in single cells, and freely specifiable digital communication
    between individual bacteria. These examples showcase the potential for real-time
    integration of theoretical models with measurement and control of many individual
    cells to investigate and engineer microbial population behavior.'
acknowledgement: We are grateful to M. Lang, H. Janovjak, M. Khammash, A. Milias-Argeitis,
  M. Rullan, G. Batt, A. Bosma-Moody, Aryan, S. Leibler, and members of the Guet and
  Tkačik groups for helpful discussion, comments, and suggestions. We thank A. Moglich,
  T. Mathes, J. Tabor, and S. Schmidl for kind gifts of strains, and R. Hauschild,
  B. Knep, M. Lang, T. Asenov, E. Papusheva, T. Menner, T. Adletzberger, and J. Merrin
  for technical assistance. The research leading to these results has received funding
  from the People Programme (Marie Curie Actions) of the European Union’s Seventh
  Framework Programme (FP7/2007–2013) under REA grant agreement no. [291734]. (to
  R.C. and J.R.), Austrian Science Fund grant FWF P28844 (to G.T.), and internal IST
  Austria Interdisciplinary Project Support. J.R. acknowledges support from the Agence
  Nationale de la Recherche (ANR) under Grant Nos. ANR-16-CE33-0018 (MEMIP), ANR-16-CE12-0025
  (COGEX) and ANR-10-BINF-06-01 (ICEBERG).
article_number: '1535'
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Remy P
  full_name: Chait, Remy P
  id: 3464AE84-F248-11E8-B48F-1D18A9856A87
  last_name: Chait
  orcid: 0000-0003-0876-3187
- first_name: Jakob
  full_name: Ruess, Jakob
  id: 4A245D00-F248-11E8-B48F-1D18A9856A87
  last_name: Ruess
  orcid: 0000-0003-1615-3282
- first_name: Tobias
  full_name: Bergmiller, Tobias
  id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
  last_name: Bergmiller
  orcid: 0000-0001-5396-4346
- first_name: Gasper
  full_name: Tkacik, Gasper
  id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
  last_name: Tkacik
  orcid: 0000-0002-6699-1455
- first_name: Calin C
  full_name: Guet, Calin C
  id: 47F8433E-F248-11E8-B48F-1D18A9856A87
  last_name: Guet
  orcid: 0000-0001-6220-2052
citation:
  ama: Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. Shaping bacterial population
    behavior through computer interfaced control of individual cells. <i>Nature Communications</i>.
    2017;8(1). doi:<a href="https://doi.org/10.1038/s41467-017-01683-1">10.1038/s41467-017-01683-1</a>
  apa: Chait, R. P., Ruess, J., Bergmiller, T., Tkačik, G., &#38; Guet, C. C. (2017).
    Shaping bacterial population behavior through computer interfaced control of individual
    cells. <i>Nature Communications</i>. Nature Publishing Group. <a href="https://doi.org/10.1038/s41467-017-01683-1">https://doi.org/10.1038/s41467-017-01683-1</a>
  chicago: Chait, Remy P, Jakob Ruess, Tobias Bergmiller, Gašper Tkačik, and Calin
    C Guet. “Shaping Bacterial Population Behavior through Computer Interfaced Control
    of Individual Cells.” <i>Nature Communications</i>. Nature Publishing Group, 2017.
    <a href="https://doi.org/10.1038/s41467-017-01683-1">https://doi.org/10.1038/s41467-017-01683-1</a>.
  ieee: R. P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, and C. C. Guet, “Shaping
    bacterial population behavior through computer interfaced control of individual
    cells,” <i>Nature Communications</i>, vol. 8, no. 1. Nature Publishing Group,
    2017.
  ista: Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. 2017. Shaping bacterial
    population behavior through computer interfaced control of individual cells. Nature
    Communications. 8(1), 1535.
  mla: Chait, Remy P., et al. “Shaping Bacterial Population Behavior through Computer
    Interfaced Control of Individual Cells.” <i>Nature Communications</i>, vol. 8,
    no. 1, 1535, Nature Publishing Group, 2017, doi:<a href="https://doi.org/10.1038/s41467-017-01683-1">10.1038/s41467-017-01683-1</a>.
  short: R.P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, C.C. Guet, Nature Communications
    8 (2017).
date_created: 2018-12-11T11:47:30Z
date_published: 2017-12-01T00:00:00Z
date_updated: 2021-01-12T08:06:15Z
day: '01'
ddc:
- '576'
- '579'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1038/s41467-017-01683-1
ec_funded: 1
file:
- access_level: open_access
  checksum: 44bb5d0229926c23a9955d9fe0f9723f
  content_type: application/pdf
  creator: system
  date_created: 2018-12-12T10:16:05Z
  date_updated: 2020-07-14T12:47:20Z
  file_id: '5190'
  file_name: IST-2017-911-v1+1_s41467-017-01683-1.pdf
  file_size: 1951699
  relation: main_file
file_date_updated: 2020-07-14T12:47:20Z
has_accepted_license: '1'
intvolume: '         8'
issue: '1'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '291734'
  name: International IST Postdoc Fellowship Programme
- _id: 254E9036-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: P28844-B27
  name: Biophysics of information processing in gene regulation
publication: Nature Communications
publication_identifier:
  issn:
  - '20411723'
publication_status: published
publisher: Nature Publishing Group
publist_id: '7191'
pubrep_id: '911'
quality_controlled: '1'
scopus_import: 1
status: public
title: Shaping bacterial population behavior through computer interfaced control of
  individual cells
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 8
year: '2017'
...
---
_id: '1332'
abstract:
- lang: eng
  text: Antibiotic-sensitive and -resistant bacteria coexist in natural environments
    with low, if detectable, antibiotic concentrations. Except possibly around localized
    antibiotic sources, where resistance can provide a strong advantage, bacterial
    fitness is dominated by stresses unaffected by resistance to the antibiotic. How
    do such mixed and heterogeneous conditions influence the selective advantage or
    disadvantage of antibiotic resistance? Here we find that sub-inhibitory levels
    of tetracyclines potentiate selection for or against tetracycline resistance around
    localized sources of almost any toxin or stress. Furthermore, certain stresses
    generate alternating rings of selection for and against resistance around a localized
    source of the antibiotic. In these conditions, localized antibiotic sources, even
    at high strengths, can actually produce a net selection against resistance to
    the antibiotic. Our results show that interactions between the effects of an antibiotic
    and other stresses in inhomogeneous environments can generate pervasive, complex
    patterns of selection both for and against antibiotic resistance.
acknowledgement: This work was partially supported by US National Institutes of Health
  grant R01-GM081617, Israeli Centers of Research Excellence I-CORE Program ISF Grant
  No. 152/11, and the European Research Council FP7 ERC Grant 281891.
article_number: '10333'
author:
- first_name: Remy P
  full_name: Chait, Remy P
  id: 3464AE84-F248-11E8-B48F-1D18A9856A87
  last_name: Chait
  orcid: 0000-0003-0876-3187
- first_name: Adam
  full_name: Palmer, Adam
  last_name: Palmer
- first_name: Idan
  full_name: Yelin, Idan
  last_name: Yelin
- first_name: Roy
  full_name: Kishony, Roy
  last_name: Kishony
citation:
  ama: Chait RP, Palmer A, Yelin I, Kishony R. Pervasive selection for and against
    antibiotic resistance in inhomogeneous multistress environments. <i>Nature Communications</i>.
    2016;7. doi:<a href="https://doi.org/10.1038/ncomms10333">10.1038/ncomms10333</a>
  apa: Chait, R. P., Palmer, A., Yelin, I., &#38; Kishony, R. (2016). Pervasive selection
    for and against antibiotic resistance in inhomogeneous multistress environments.
    <i>Nature Communications</i>. Nature Publishing Group. <a href="https://doi.org/10.1038/ncomms10333">https://doi.org/10.1038/ncomms10333</a>
  chicago: Chait, Remy P, Adam Palmer, Idan Yelin, and Roy Kishony. “Pervasive Selection
    for and against Antibiotic Resistance in Inhomogeneous Multistress Environments.”
    <i>Nature Communications</i>. Nature Publishing Group, 2016. <a href="https://doi.org/10.1038/ncomms10333">https://doi.org/10.1038/ncomms10333</a>.
  ieee: R. P. Chait, A. Palmer, I. Yelin, and R. Kishony, “Pervasive selection for
    and against antibiotic resistance in inhomogeneous multistress environments,”
    <i>Nature Communications</i>, vol. 7. Nature Publishing Group, 2016.
  ista: Chait RP, Palmer A, Yelin I, Kishony R. 2016. Pervasive selection for and
    against antibiotic resistance in inhomogeneous multistress environments. Nature
    Communications. 7, 10333.
  mla: Chait, Remy P., et al. “Pervasive Selection for and against Antibiotic Resistance
    in Inhomogeneous Multistress Environments.” <i>Nature Communications</i>, vol.
    7, 10333, Nature Publishing Group, 2016, doi:<a href="https://doi.org/10.1038/ncomms10333">10.1038/ncomms10333</a>.
  short: R.P. Chait, A. Palmer, I. Yelin, R. Kishony, Nature Communications 7 (2016).
date_created: 2018-12-11T11:51:25Z
date_published: 2016-01-20T00:00:00Z
date_updated: 2021-01-12T06:49:57Z
day: '20'
ddc:
- '570'
- '579'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1038/ncomms10333
file:
- access_level: open_access
  checksum: ef147bcbb8bd37e9079cf3ce06f5815d
  content_type: application/pdf
  creator: system
  date_created: 2018-12-12T10:13:52Z
  date_updated: 2020-07-14T12:44:44Z
  file_id: '5039'
  file_name: IST-2016-662-v1+1_ncomms10333.pdf
  file_size: 1844107
  relation: main_file
file_date_updated: 2020-07-14T12:44:44Z
has_accepted_license: '1'
intvolume: '         7'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
publication: Nature Communications
publication_status: published
publisher: Nature Publishing Group
publist_id: '5936'
pubrep_id: '662'
quality_controlled: '1'
scopus_import: 1
status: public
title: Pervasive selection for and against antibiotic resistance in inhomogeneous
  multistress environments
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 7
year: '2016'
...
---
_id: '1342'
abstract:
- lang: eng
  text: A key aspect of bacterial survival is the ability to evolve while migrating
    across spatially varying environmental challenges. Laboratory experiments, however,
    often study evolution in well-mixed systems. Here, we introduce an experimental
    device, the microbial evolution and growth arena (MEGA)-plate, in which bacteria
    spread and evolved on a large antibiotic landscape (120 × 60 centimeters) that
    allowed visual observation of mutation and selection in a migrating bacterial
    front.While resistance increased consistently, multiple coexisting lineages diversified
    both phenotypically and genotypically. Analyzing mutants at and behind the propagating
    front,we found that evolution is not always led by the most resistant mutants;
    highly resistant mutants may be trapped behindmore sensitive lineages.TheMEGA-plate
    provides a versatile platformfor studying microbial adaption and directly visualizing
    evolutionary dynamics.
author:
- first_name: Michael
  full_name: Baym, Michael
  last_name: Baym
- first_name: Tami
  full_name: Lieberman, Tami
  last_name: Lieberman
- first_name: Eric
  full_name: Kelsic, Eric
  last_name: Kelsic
- first_name: Remy P
  full_name: Chait, Remy P
  id: 3464AE84-F248-11E8-B48F-1D18A9856A87
  last_name: Chait
  orcid: 0000-0003-0876-3187
- first_name: Rotem
  full_name: Gross, Rotem
  last_name: Gross
- first_name: Idan
  full_name: Yelin, Idan
  last_name: Yelin
- first_name: Roy
  full_name: Kishony, Roy
  last_name: Kishony
citation:
  ama: Baym M, Lieberman T, Kelsic E, et al. Spatiotemporal microbial evolution on
    antibiotic landscapes. <i>Science</i>. 2016;353(6304):1147-1151. doi:<a href="https://doi.org/10.1126/science.aag0822">10.1126/science.aag0822</a>
  apa: Baym, M., Lieberman, T., Kelsic, E., Chait, R. P., Gross, R., Yelin, I., &#38;
    Kishony, R. (2016). Spatiotemporal microbial evolution on antibiotic landscapes.
    <i>Science</i>. American Association for the Advancement of Science. <a href="https://doi.org/10.1126/science.aag0822">https://doi.org/10.1126/science.aag0822</a>
  chicago: Baym, Michael, Tami Lieberman, Eric Kelsic, Remy P Chait, Rotem Gross,
    Idan Yelin, and Roy Kishony. “Spatiotemporal Microbial Evolution on Antibiotic
    Landscapes.” <i>Science</i>. American Association for the Advancement of Science,
    2016. <a href="https://doi.org/10.1126/science.aag0822">https://doi.org/10.1126/science.aag0822</a>.
  ieee: M. Baym <i>et al.</i>, “Spatiotemporal microbial evolution on antibiotic landscapes,”
    <i>Science</i>, vol. 353, no. 6304. American Association for the Advancement of
    Science, pp. 1147–1151, 2016.
  ista: Baym M, Lieberman T, Kelsic E, Chait RP, Gross R, Yelin I, Kishony R. 2016.
    Spatiotemporal microbial evolution on antibiotic landscapes. Science. 353(6304),
    1147–1151.
  mla: Baym, Michael, et al. “Spatiotemporal Microbial Evolution on Antibiotic Landscapes.”
    <i>Science</i>, vol. 353, no. 6304, American Association for the Advancement of
    Science, 2016, pp. 1147–51, doi:<a href="https://doi.org/10.1126/science.aag0822">10.1126/science.aag0822</a>.
  short: M. Baym, T. Lieberman, E. Kelsic, R.P. Chait, R. Gross, I. Yelin, R. Kishony,
    Science 353 (2016) 1147–1151.
date_created: 2018-12-11T11:51:29Z
date_published: 2016-09-09T00:00:00Z
date_updated: 2021-01-12T06:50:01Z
day: '09'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1126/science.aag0822
intvolume: '       353'
issue: '6304'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5534434/
month: '09'
oa: 1
oa_version: Preprint
page: 1147 - 1151
publication: Science
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '5911'
quality_controlled: '1'
scopus_import: 1
status: public
title: Spatiotemporal microbial evolution on antibiotic landscapes
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 353
year: '2016'
...
---
_id: '1290'
abstract:
- lang: eng
  text: We developed a competition-based screening strategy to identify compounds
    that invert the selective advantage of antibiotic resistance. Using our assay,
    we screened over 19,000 compounds for the ability to select against the TetA tetracycline-resistance
    efflux pump in Escherichia coli and identified two hits, β-thujaplicin and disulfiram.
    Treating a tetracycline-resistant population with β-thujaplicin selects for loss
    of the resistance gene, enabling an effective second-phase treatment with doxycycline.
acknowledgement: "This work was supported in part by National Institute of Allergy
  and Infectious Diseases grant U54 AI057159, US National Institutes of Health grants
  R01 GM081617 (to R.K.) and GM086258 (to J.C.), European Research Council FP7 ERC
  grant 281891 (to R.K.) and a National Science Foundation Graduate Fellowship (to
  L.K.S.).\r\n"
author:
- first_name: Laura
  full_name: Stone, Laura
  last_name: Stone
- first_name: Michael
  full_name: Baym, Michael
  last_name: Baym
- first_name: Tami
  full_name: Lieberman, Tami
  last_name: Lieberman
- first_name: Remy P
  full_name: Chait, Remy P
  id: 3464AE84-F248-11E8-B48F-1D18A9856A87
  last_name: Chait
  orcid: 0000-0003-0876-3187
- first_name: Jon
  full_name: Clardy, Jon
  last_name: Clardy
- first_name: Roy
  full_name: Kishony, Roy
  last_name: Kishony
citation:
  ama: Stone L, Baym M, Lieberman T, Chait RP, Clardy J, Kishony R. Compounds that
    select against the tetracycline-resistance efflux pump. <i>Nature Chemical Biology</i>.
    2016;12(11):902-904. doi:<a href="https://doi.org/10.1038/nchembio.2176">10.1038/nchembio.2176</a>
  apa: Stone, L., Baym, M., Lieberman, T., Chait, R. P., Clardy, J., &#38; Kishony,
    R. (2016). Compounds that select against the tetracycline-resistance efflux pump.
    <i>Nature Chemical Biology</i>. Nature Publishing Group. <a href="https://doi.org/10.1038/nchembio.2176">https://doi.org/10.1038/nchembio.2176</a>
  chicago: Stone, Laura, Michael Baym, Tami Lieberman, Remy P Chait, Jon Clardy, and
    Roy Kishony. “Compounds That Select against the Tetracycline-Resistance Efflux
    Pump.” <i>Nature Chemical Biology</i>. Nature Publishing Group, 2016. <a href="https://doi.org/10.1038/nchembio.2176">https://doi.org/10.1038/nchembio.2176</a>.
  ieee: L. Stone, M. Baym, T. Lieberman, R. P. Chait, J. Clardy, and R. Kishony, “Compounds
    that select against the tetracycline-resistance efflux pump,” <i>Nature Chemical
    Biology</i>, vol. 12, no. 11. Nature Publishing Group, pp. 902–904, 2016.
  ista: Stone L, Baym M, Lieberman T, Chait RP, Clardy J, Kishony R. 2016. Compounds
    that select against the tetracycline-resistance efflux pump. Nature Chemical Biology.
    12(11), 902–904.
  mla: Stone, Laura, et al. “Compounds That Select against the Tetracycline-Resistance
    Efflux Pump.” <i>Nature Chemical Biology</i>, vol. 12, no. 11, Nature Publishing
    Group, 2016, pp. 902–04, doi:<a href="https://doi.org/10.1038/nchembio.2176">10.1038/nchembio.2176</a>.
  short: L. Stone, M. Baym, T. Lieberman, R.P. Chait, J. Clardy, R. Kishony, Nature
    Chemical Biology 12 (2016) 902–904.
date_created: 2018-12-11T11:51:10Z
date_published: 2016-11-01T00:00:00Z
date_updated: 2021-01-12T06:49:39Z
day: '01'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1038/nchembio.2176
intvolume: '        12'
issue: '11'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069154/
month: '11'
oa: 1
oa_version: Preprint
page: 902 - 904
publication: Nature Chemical Biology
publication_status: published
publisher: Nature Publishing Group
publist_id: '6026'
quality_controlled: '1'
scopus_import: 1
status: public
title: Compounds that select against the tetracycline-resistance efflux pump
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 12
year: '2016'
...
---
_id: '499'
abstract:
- lang: eng
  text: Exposure of an isogenic bacterial population to a cidal antibiotic typically
    fails to eliminate a small fraction of refractory cells. Historically, fractional
    killing has been attributed to infrequently dividing or nondividing &quot;persisters.&quot;
    Using microfluidic cultures and time-lapse microscopy, we found that Mycobacterium
    smegmatis persists by dividing in the presence of the drug isoniazid (INH). Although
    persistence in these studies was characterized by stable numbers of cells, this
    apparent stability was actually a dynamic state of balanced division and death.
    Single cells expressed catalase-peroxidase (KatG), which activates INH, in stochastic
    pulses that were negatively correlated with cell survival. These behaviors may
    reflect epigenetic effects, because KatG pulsing and death were correlated between
    sibling cells. Selection of lineages characterized by infrequent KatG pulsing
    could allow nonresponsive adaptation during prolonged drug exposure.
author:
- first_name: Yurichi
  full_name: Wakamoto, Yurichi
  last_name: Wakamoto
- first_name: Neraaj
  full_name: Dhar, Neraaj
  last_name: Dhar
- first_name: Remy P
  full_name: Chait, Remy P
  id: 3464AE84-F248-11E8-B48F-1D18A9856A87
  last_name: Chait
  orcid: 0000-0003-0876-3187
- first_name: Katrin
  full_name: Schneider, Katrin
  last_name: Schneider
- first_name: François
  full_name: Signorino Gelo, François
  last_name: Signorino Gelo
- first_name: Stanislas
  full_name: Leibler, Stanislas
  last_name: Leibler
- first_name: John
  full_name: Mckinney, John
  last_name: Mckinney
citation:
  ama: Wakamoto Y, Dhar N, Chait RP, et al. Dynamic persistence of antibiotic-stressed
    mycobacteria. <i>Science</i>. 2013;339(6115):91-95. doi:<a href="https://doi.org/10.1126/science.1229858">10.1126/science.1229858</a>
  apa: Wakamoto, Y., Dhar, N., Chait, R. P., Schneider, K., Signorino Gelo, F., Leibler,
    S., &#38; Mckinney, J. (2013). Dynamic persistence of antibiotic-stressed mycobacteria.
    <i>Science</i>. American Association for the Advancement of Science. <a href="https://doi.org/10.1126/science.1229858">https://doi.org/10.1126/science.1229858</a>
  chicago: Wakamoto, Yurichi, Neraaj Dhar, Remy P Chait, Katrin Schneider, François
    Signorino Gelo, Stanislas Leibler, and John Mckinney. “Dynamic Persistence of
    Antibiotic-Stressed Mycobacteria.” <i>Science</i>. American Association for the
    Advancement of Science, 2013. <a href="https://doi.org/10.1126/science.1229858">https://doi.org/10.1126/science.1229858</a>.
  ieee: Y. Wakamoto <i>et al.</i>, “Dynamic persistence of antibiotic-stressed mycobacteria,”
    <i>Science</i>, vol. 339, no. 6115. American Association for the Advancement of
    Science, pp. 91–95, 2013.
  ista: Wakamoto Y, Dhar N, Chait RP, Schneider K, Signorino Gelo F, Leibler S, Mckinney
    J. 2013. Dynamic persistence of antibiotic-stressed mycobacteria. Science. 339(6115),
    91–95.
  mla: Wakamoto, Yurichi, et al. “Dynamic Persistence of Antibiotic-Stressed Mycobacteria.”
    <i>Science</i>, vol. 339, no. 6115, American Association for the Advancement of
    Science, 2013, pp. 91–95, doi:<a href="https://doi.org/10.1126/science.1229858">10.1126/science.1229858</a>.
  short: Y. Wakamoto, N. Dhar, R.P. Chait, K. Schneider, F. Signorino Gelo, S. Leibler,
    J. Mckinney, Science 339 (2013) 91–95.
date_created: 2018-12-11T11:46:48Z
date_published: 2013-01-04T00:00:00Z
date_updated: 2021-01-12T08:01:06Z
day: '04'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1126/science.1229858
intvolume: '       339'
issue: '6115'
language:
- iso: eng
month: '01'
oa_version: None
page: 91 - 95
publication: Science
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '7321'
quality_controlled: '1'
scopus_import: 1
status: public
title: Dynamic persistence of antibiotic-stressed mycobacteria
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 339
year: '2013'
...
---
_id: '4228'
abstract:
- lang: eng
  text: Suppressive drug interactions, in which one antibiotic can actually help bacterial
    cells to grow faster in the presence of another, occur between protein and DNA
    synthesis inhibitors. Here, we show that this suppression results from nonoptimal
    regulation of ribosomal genes in the presence of DNA stress. Using GFP-tagged
    transcription reporters in Escherichia coli, we find that ribosomal genes are
    not directly regulated by DNA stress, leading to an imbalance between cellular
    DNA and protein content. To test whether ribosomal gene expression under DNA stress
    is nonoptimal for growth rate, we sequentially deleted up to six of the seven
    ribosomal RNA operons. These synthetic manipulations of ribosomal gene expression
    correct the protein-DNA imbalance, lead to improved survival and growth, and completely
    remove the suppressive drug interaction. A simple mathematical model explains
    the nonoptimal regulation in different nutrient environments. These results reveal
    the genetic mechanism underlying an important class of suppressive drug interactions.
author:
- first_name: Tobias
  full_name: Bollenbach, Tobias
  last_name: Bollenbach
- first_name: Selwyn
  full_name: Quan, Selwyn
  last_name: Quan
- first_name: Remy P
  full_name: Remy Chait
  id: 3464AE84-F248-11E8-B48F-1D18A9856A87
  last_name: Chait
  orcid: 0000-0003-0876-3187
- first_name: Roy
  full_name: Kishony, Roy
  last_name: Kishony
citation:
  ama: Bollenbach T, Quan S, Chait RP, Kishony R. Nonoptimal Microbial Response to
    Antibiotics Underlies Suppressive Drug Interactions. <i>Cell</i>. 2009;139(4):707-718.
    doi:<a href="https://doi.org/10.1016/j.cell.2009.10.025">10.1016/j.cell.2009.10.025</a>
  apa: Bollenbach, T., Quan, S., Chait, R. P., &#38; Kishony, R. (2009). Nonoptimal
    Microbial Response to Antibiotics Underlies Suppressive Drug Interactions. <i>Cell</i>.
    Cell Press. <a href="https://doi.org/10.1016/j.cell.2009.10.025">https://doi.org/10.1016/j.cell.2009.10.025</a>
  chicago: Bollenbach, Tobias, Selwyn Quan, Remy P Chait, and Roy Kishony. “Nonoptimal
    Microbial Response to Antibiotics Underlies Suppressive Drug Interactions.” <i>Cell</i>.
    Cell Press, 2009. <a href="https://doi.org/10.1016/j.cell.2009.10.025">https://doi.org/10.1016/j.cell.2009.10.025</a>.
  ieee: T. Bollenbach, S. Quan, R. P. Chait, and R. Kishony, “Nonoptimal Microbial
    Response to Antibiotics Underlies Suppressive Drug Interactions,” <i>Cell</i>,
    vol. 139, no. 4. Cell Press, pp. 707–718, 2009.
  ista: Bollenbach T, Quan S, Chait RP, Kishony R. 2009. Nonoptimal Microbial Response
    to Antibiotics Underlies Suppressive Drug Interactions. Cell. 139(4), 707–718.
  mla: Bollenbach, Tobias, et al. “Nonoptimal Microbial Response to Antibiotics Underlies
    Suppressive Drug Interactions.” <i>Cell</i>, vol. 139, no. 4, Cell Press, 2009,
    pp. 707–18, doi:<a href="https://doi.org/10.1016/j.cell.2009.10.025">10.1016/j.cell.2009.10.025</a>.
  short: T. Bollenbach, S. Quan, R.P. Chait, R. Kishony, Cell 139 (2009) 707–718.
date_created: 2018-12-11T12:07:43Z
date_published: 2009-01-01T00:00:00Z
date_updated: 2021-01-12T07:55:27Z
day: '01'
doi: 10.1016/j.cell.2009.10.025
extern: 1
intvolume: '       139'
issue: '4'
month: '01'
page: 707 - 718
publication: Cell
publication_status: published
publisher: Cell Press
publist_id: '1890'
quality_controlled: 0
status: public
title: Nonoptimal Microbial Response to Antibiotics Underlies Suppressive Drug Interactions
type: journal_article
volume: 139
year: '2009'
...