---
_id: '11339'
abstract:
- lang: eng
text: The interaction between a cell and its environment shapes fundamental intracellular
processes such as cellular metabolism. In most cases growth rate is treated as
a proximal metric for understanding the cellular metabolic status. However, changes
in growth rate might not reflect metabolic variations in individuals responding
to environmental fluctuations. Here we use single-cell microfluidics-microscopy
combined with transcriptomics, proteomics and mathematical modelling to quantify
the accumulation of glucose within Escherichia coli cells. In contrast to the
current consensus, we reveal that environmental conditions which are comparatively
unfavourable for growth, where both nutrients and salinity are depleted, increase
glucose accumulation rates in individual bacteria and population subsets. We find
that these changes in metabolic function are underpinned by variations at the
translational and posttranslational level but not at the transcriptional level
and are not dictated by changes in cell size. The metabolic response-characteristics
identified greatly advance our fundamental understanding of the interactions between
bacteria and their environment and have important ramifications when investigating
cellular processes where salinity plays an important role.
acknowledgement: G.G. was supported by an EPSRC DTP PhD studentship (EP/M506527/1).
M.V. and K.T.A. gratefully acknowledge financial support from the EPSRC (EP/N014391/1).
U.L. was supported through a BBSRC grant (BB/V008021/1) and an MRC Proximity to
Discovery EXCITEME2 grant (MCPC17189). This work was further supported by a Royal
Society Research Grant (RG180007) awarded to S.P. and a QUEX Initiator grant awarded
to S.P. and K.T.A.. D.S.M., T.A.R. and S.P.’s work in this area is also supported
by a Marie Skłodowska-Curie project SINGEK (H2020-MSCA-ITN-2015-675752) and the
Gordon and Betty Moore Foundation Marine Microbiology Initiative (GBMF5514). B.M.I.
acknowledges support from a Wellcome Trust Institutional Strategic Support Award
to the University of Exeter (204909/Z/16/Z). This project utilised equipment funded
by the Wellcome Trust Institutional Strategic Support Fund (WT097835MF), Wellcome
Trust Multi User Equipment Award (WT101650MA) and BBSRC LOLA award (BB/K003240/1).
article_number: '385'
article_processing_charge: No
article_type: original
author:
- first_name: Georgina
full_name: Glover, Georgina
last_name: Glover
- first_name: Margaritis
full_name: Voliotis, Margaritis
last_name: Voliotis
- first_name: Urszula
full_name: Łapińska, Urszula
last_name: Łapińska
- first_name: Brandon M.
full_name: Invergo, Brandon M.
last_name: Invergo
- first_name: Darren
full_name: Soanes, Darren
last_name: Soanes
- first_name: Paul
full_name: O’Neill, Paul
last_name: O’Neill
- first_name: Karen
full_name: Moore, Karen
last_name: Moore
- first_name: Nela
full_name: Nikolic, Nela
id: 42D9CABC-F248-11E8-B48F-1D18A9856A87
last_name: Nikolic
orcid: 0000-0001-9068-6090
- first_name: Peter
full_name: Petrov, Peter
last_name: Petrov
- first_name: David S.
full_name: Milner, David S.
last_name: Milner
- first_name: Sumita
full_name: Roy, Sumita
last_name: Roy
- first_name: Kate
full_name: Heesom, Kate
last_name: Heesom
- first_name: Thomas A.
full_name: Richards, Thomas A.
last_name: Richards
- first_name: Krasimira
full_name: Tsaneva-Atanasova, Krasimira
last_name: Tsaneva-Atanasova
- first_name: Stefano
full_name: Pagliara, Stefano
last_name: Pagliara
citation:
ama: Glover G, Voliotis M, Łapińska U, et al. Nutrient and salt depletion synergistically
boosts glucose metabolism in individual Escherichia coli cells. Communications
Biology. 2022;5. doi:10.1038/s42003-022-03336-6
apa: Glover, G., Voliotis, M., Łapińska, U., Invergo, B. M., Soanes, D., O’Neill,
P., … Pagliara, S. (2022). Nutrient and salt depletion synergistically boosts
glucose metabolism in individual Escherichia coli cells. Communications Biology.
Springer Nature. https://doi.org/10.1038/s42003-022-03336-6
chicago: Glover, Georgina, Margaritis Voliotis, Urszula Łapińska, Brandon M. Invergo,
Darren Soanes, Paul O’Neill, Karen Moore, et al. “Nutrient and Salt Depletion
Synergistically Boosts Glucose Metabolism in Individual Escherichia Coli Cells.”
Communications Biology. Springer Nature, 2022. https://doi.org/10.1038/s42003-022-03336-6.
ieee: G. Glover et al., “Nutrient and salt depletion synergistically boosts
glucose metabolism in individual Escherichia coli cells,” Communications Biology,
vol. 5. Springer Nature, 2022.
ista: Glover G, Voliotis M, Łapińska U, Invergo BM, Soanes D, O’Neill P, Moore K,
Nikolic N, Petrov P, Milner DS, Roy S, Heesom K, Richards TA, Tsaneva-Atanasova
K, Pagliara S. 2022. Nutrient and salt depletion synergistically boosts glucose
metabolism in individual Escherichia coli cells. Communications Biology. 5, 385.
mla: Glover, Georgina, et al. “Nutrient and Salt Depletion Synergistically Boosts
Glucose Metabolism in Individual Escherichia Coli Cells.” Communications Biology,
vol. 5, 385, Springer Nature, 2022, doi:10.1038/s42003-022-03336-6.
short: G. Glover, M. Voliotis, U. Łapińska, B.M. Invergo, D. Soanes, P. O’Neill,
K. Moore, N. Nikolic, P. Petrov, D.S. Milner, S. Roy, K. Heesom, T.A. Richards,
K. Tsaneva-Atanasova, S. Pagliara, Communications Biology 5 (2022).
date_created: 2022-05-01T22:01:41Z
date_published: 2022-04-20T00:00:00Z
date_updated: 2023-08-03T06:45:26Z
day: '20'
ddc:
- '570'
department:
- _id: CaGu
doi: 10.1038/s42003-022-03336-6
external_id:
isi:
- '000784143400001'
pmid:
- '35444215'
file:
- access_level: open_access
checksum: 7c6f76ab17393d650825cc240edc84b3
content_type: application/pdf
creator: dernst
date_created: 2022-05-02T06:26:26Z
date_updated: 2022-05-02T06:26:26Z
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file_name: 2022_CommBiology_Glover.pdf
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isi: 1
language:
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month: '04'
oa: 1
oa_version: Published Version
pmid: 1
publication: Communications Biology
publication_identifier:
eissn:
- 2399-3642
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Nutrient and salt depletion synergistically boosts glucose metabolism in individual
Escherichia coli 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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 5
year: '2022'
...
---
_id: '11713'
abstract:
- lang: eng
text: "Objective: MazF is a sequence-specific endoribonuclease-toxin of the MazEF
toxin–antitoxin system. MazF cleaves single-stranded ribonucleic acid (RNA) regions
at adenine–cytosine–adenine (ACA) sequences in the bacterium Escherichia coli.
The MazEF system has been used in various biotechnology and synthetic biology
applications. In this study, we infer how ectopic mazF overexpression affects
production of heterologous proteins. To this end, we quantified the levels of
fluorescent proteins expressed in E. coli from reporters translated from the ACA-containing
or ACA-less messenger RNAs (mRNAs). Additionally, we addressed the impact of the
5′-untranslated region of these reporter mRNAs under the same conditions by comparing
expression from mRNAs that comprise (canonical mRNA) or lack this region (leaderless
mRNA).\r\nResults: Flow cytometry analysis indicates that during mazF overexpression,
fluorescent proteins are translated from the canonical as well as leaderless mRNAs.
Our analysis further indicates that longer mazF overexpression generally increases
the concentration of fluorescent proteins translated from ACA-less mRNAs, however
it also substantially increases bacterial population heterogeneity. Finally, our
results suggest that the strength and duration of mazF overexpression should be
optimized for each experimental setup, to maximize the heterologous protein production
and minimize the amount of phenotypic heterogeneity in bacterial populations,
which is unfavorable in biotechnological processes."
acknowledgement: "We acknowledge the Max Perutz Labs FACS Facility together with Thomas
Sauer. NN is grateful to Călin C. Guet for his support.\r\nThis work was funded
by the Elise Richter grant V738 of the Austrian Science Fund (FWF), and the FWF
Lise Meitner grant M1697, to NN; and by the FWF grant P22249, FWF Special Research
Program RNA-REG F43 (subproject F4316), and FWF doctoral program RNA Biology (W1207),
to IM. Open access funding provided by the Austrian Science Fund."
article_number: '173'
article_processing_charge: No
article_type: letter_note
author:
- first_name: Nela
full_name: Nikolic, Nela
id: 42D9CABC-F248-11E8-B48F-1D18A9856A87
last_name: Nikolic
orcid: 0000-0001-9068-6090
- first_name: Martina
full_name: Sauert, Martina
last_name: Sauert
- first_name: Tanino G.
full_name: Albanese, Tanino G.
last_name: Albanese
- first_name: Isabella
full_name: Moll, Isabella
last_name: Moll
citation:
ama: Nikolic N, Sauert M, Albanese TG, Moll I. Quantifying heterologous gene expression
during ectopic MazF production in Escherichia coli. BMC Research Notes.
2022;15. doi:10.1186/s13104-022-06061-9
apa: Nikolic, N., Sauert, M., Albanese, T. G., & Moll, I. (2022). Quantifying
heterologous gene expression during ectopic MazF production in Escherichia coli.
BMC Research Notes. Springer Nature. https://doi.org/10.1186/s13104-022-06061-9
chicago: Nikolic, Nela, Martina Sauert, Tanino G. Albanese, and Isabella Moll. “Quantifying
Heterologous Gene Expression during Ectopic MazF Production in Escherichia Coli.”
BMC Research Notes. Springer Nature, 2022. https://doi.org/10.1186/s13104-022-06061-9.
ieee: N. Nikolic, M. Sauert, T. G. Albanese, and I. Moll, “Quantifying heterologous
gene expression during ectopic MazF production in Escherichia coli,” BMC Research
Notes, vol. 15. Springer Nature, 2022.
ista: Nikolic N, Sauert M, Albanese TG, Moll I. 2022. Quantifying heterologous gene
expression during ectopic MazF production in Escherichia coli. BMC Research Notes.
15, 173.
mla: Nikolic, Nela, et al. “Quantifying Heterologous Gene Expression during Ectopic
MazF Production in Escherichia Coli.” BMC Research Notes, vol. 15, 173,
Springer Nature, 2022, doi:10.1186/s13104-022-06061-9.
short: N. Nikolic, M. Sauert, T.G. Albanese, I. Moll, BMC Research Notes 15 (2022).
date_created: 2022-08-01T09:04:27Z
date_published: 2022-05-13T00:00:00Z
date_updated: 2022-08-01T09:27:40Z
day: '13'
ddc:
- '570'
department:
- _id: CaGu
doi: 10.1186/s13104-022-06061-9
external_id:
pmid:
- '35562780'
file:
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checksum: 008156e5340e9789f0f6d82bde4d347a
content_type: application/pdf
creator: dernst
date_created: 2022-08-01T09:24:42Z
date_updated: 2022-08-01T09:24:42Z
file_id: '11714'
file_name: 2022_BMCResearchNotes_Nikolic.pdf
file_size: 1545310
relation: main_file
success: 1
file_date_updated: 2022-08-01T09:24:42Z
has_accepted_license: '1'
intvolume: ' 15'
keyword:
- General Biochemistry
- Genetics and Molecular Biology
- General Medicine
language:
- iso: eng
month: '05'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 26956E74-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: V00738
name: Bacterial toxin-antitoxin systems as antiphage defense mechanisms
publication: BMC Research Notes
publication_identifier:
issn:
- 1756-0500
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
link:
- relation: erratum
url: https://doi.org/10.1186/s13104-022-06152-7
scopus_import: '1'
status: public
title: Quantifying heterologous gene expression during ectopic MazF production in
Escherichia coli
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: 15
year: '2022'
...
---
_id: '138'
abstract:
- lang: eng
text: Autoregulation is the direct modulation of gene expression by the product
of the corresponding gene. Autoregulation of bacterial gene expression has been
mostly studied at the transcriptional level, when a protein acts as the cognate
transcriptional repressor. A recent study investigating dynamics of the bacterial
toxin–antitoxin MazEF system has shown how autoregulation at both the transcriptional
and post-transcriptional levels affects the heterogeneity of Escherichia coli
populations. Toxin–antitoxin systems hold a crucial but still elusive part in
bacterial response to stress. This perspective highlights how these modules can
also serve as a great model system for investigating basic concepts in gene regulation.
However, as the genomic background and environmental conditions substantially
influence toxin activation, it is important to study (auto)regulation of toxin–antitoxin
systems in well-defined setups as well as in conditions that resemble the environmental
niche.
article_processing_charge: Yes (via OA deal)
author:
- first_name: Nela
full_name: Nikolic, Nela
id: 42D9CABC-F248-11E8-B48F-1D18A9856A87
last_name: Nikolic
orcid: 0000-0001-9068-6090
citation:
ama: 'Nikolic N. Autoregulation of bacterial gene expression: lessons from the MazEF
toxin–antitoxin system. Current Genetics. 2019;65(1):133-138. doi:10.1007/s00294-018-0879-8'
apa: 'Nikolic, N. (2019). Autoregulation of bacterial gene expression: lessons from
the MazEF toxin–antitoxin system. Current Genetics. Springer. https://doi.org/10.1007/s00294-018-0879-8'
chicago: 'Nikolic, Nela. “Autoregulation of Bacterial Gene Expression: Lessons from
the MazEF Toxin–Antitoxin System.” Current Genetics. Springer, 2019. https://doi.org/10.1007/s00294-018-0879-8.'
ieee: 'N. Nikolic, “Autoregulation of bacterial gene expression: lessons from the
MazEF toxin–antitoxin system,” Current Genetics, vol. 65, no. 1. Springer,
pp. 133–138, 2019.'
ista: 'Nikolic N. 2019. Autoregulation of bacterial gene expression: lessons from
the MazEF toxin–antitoxin system. Current Genetics. 65(1), 133–138.'
mla: 'Nikolic, Nela. “Autoregulation of Bacterial Gene Expression: Lessons from
the MazEF Toxin–Antitoxin System.” Current Genetics, vol. 65, no. 1, Springer,
2019, pp. 133–38, doi:10.1007/s00294-018-0879-8.'
short: N. Nikolic, Current Genetics 65 (2019) 133–138.
date_created: 2018-12-11T11:44:50Z
date_published: 2019-02-01T00:00:00Z
date_updated: 2023-09-08T13:23:42Z
day: '01'
ddc:
- '570'
department:
- _id: CaGu
doi: 10.1007/s00294-018-0879-8
ec_funded: 1
external_id:
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- '000456958800017'
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file_name: 2019_CurrentGenetics_Nikolic.pdf
file_size: 776399
relation: main_file
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intvolume: ' 65'
isi: 1
issue: '1'
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: 133-138
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Current Genetics
publication_status: published
publisher: Springer
publist_id: '7785'
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Autoregulation of bacterial gene expression: lessons from the MazEF toxin–antitoxin
system'
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: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 65
year: '2019'
...
---
_id: '5569'
abstract:
- lang: eng
text: "Nela Nikolic, Tobias Bergmiller, Alexandra Vandervelde, Tanino G. Albanese,
Lendert Gelens, and Isabella Moll (2018)\r\n“Autoregulation of mazEF expression
underlies growth heterogeneity in bacterial populations” Nucleic Acids Research,
doi: 10.15479/AT:ISTA:74;\r\nmicroscopy experiments by Tobias Bergmiller; image
and data analysis by Nela Nikolic."
article_processing_charge: No
author:
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Nela
full_name: Nikolic, Nela
id: 42D9CABC-F248-11E8-B48F-1D18A9856A87
last_name: Nikolic
orcid: 0000-0001-9068-6090
citation:
ama: Bergmiller T, Nikolic N. Time-lapse microscopy data. 2018. doi:10.15479/AT:ISTA:74
apa: Bergmiller, T., & Nikolic, N. (2018). Time-lapse microscopy data. Institute
of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:74
chicago: Bergmiller, Tobias, and Nela Nikolic. “Time-Lapse Microscopy Data.” Institute
of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:74.
ieee: T. Bergmiller and N. Nikolic, “Time-lapse microscopy data.” Institute of Science
and Technology Austria, 2018.
ista: Bergmiller T, Nikolic N. 2018. Time-lapse microscopy data, Institute of Science
and Technology Austria, 10.15479/AT:ISTA:74.
mla: Bergmiller, Tobias, and Nela Nikolic. Time-Lapse Microscopy Data. Institute
of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:74.
short: T. Bergmiller, N. Nikolic, (2018).
datarep_id: '74'
date_created: 2018-12-12T12:31:35Z
date_published: 2018-02-07T00:00:00Z
date_updated: 2024-02-21T13:44:45Z
day: '07'
ddc:
- '579'
department:
- _id: CaGu
doi: 10.15479/AT:ISTA:74
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checksum: 61ebb92213cfffeba3ddbaff984b81af
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has_accepted_license: '1'
keyword:
- microscopy
- microfluidics
license: https://creativecommons.org/publicdomain/zero/1.0/
month: '02'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
publist_id: '7385'
related_material:
record:
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relation: research_paper
status: public
status: public
title: Time-lapse microscopy data
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2018'
...
---
_id: '438'
abstract:
- lang: eng
text: The MazF toxin sequence-specifically cleaves single-stranded RNA upon various
stressful conditions, and it is activated as a part of the mazEF toxin–antitoxin
module in Escherichia coli. Although autoregulation of mazEF expression through
the MazE antitoxin-dependent transcriptional repression has been biochemically
characterized, less is known about post-transcriptional autoregulation, as well
as how both of these autoregulatory features affect growth of single cells during
conditions that promote MazF production. Here, we demonstrate post-transcriptional
autoregulation of mazF expression dynamics by MazF cleaving its own transcript.
Single-cell analyses of bacterial populations during ectopic MazF production indicated
that two-level autoregulation of mazEF expression influences cell-to-cell growth
rate heterogeneity. The increase in growth rate heterogeneity is governed by the
MazE antitoxin, and tuned by the MazF-dependent mazF mRNA cleavage. Also, both
autoregulatory features grant rapid exit from the stress caused by mazF overexpression.
Time-lapse microscopy revealed that MazF-mediated cleavage of mazF mRNA leads
to increased temporal variability in length of individual cells during ectopic
mazF overexpression, as explained by a stochastic model indicating that mazEF
mRNA cleavage underlies temporal fluctuations in MazF levels during stress.
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Nela
full_name: Nikolic, Nela
id: 42D9CABC-F248-11E8-B48F-1D18A9856A87
last_name: Nikolic
orcid: 0000-0001-9068-6090
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Alexandra
full_name: Vandervelde, Alexandra
last_name: Vandervelde
- first_name: Tanino
full_name: Albanese, Tanino
last_name: Albanese
- first_name: Lendert
full_name: Gelens, Lendert
last_name: Gelens
- first_name: Isabella
full_name: Moll, Isabella
last_name: Moll
citation:
ama: Nikolic N, Bergmiller T, Vandervelde A, Albanese T, Gelens L, Moll I. Autoregulation
of mazEF expression underlies growth heterogeneity in bacterial populations. Nucleic
Acids Research. 2018;46(6):2918-2931. doi:10.1093/nar/gky079
apa: Nikolic, N., Bergmiller, T., Vandervelde, A., Albanese, T., Gelens, L., &
Moll, I. (2018). Autoregulation of mazEF expression underlies growth heterogeneity
in bacterial populations. Nucleic Acids Research. Oxford University Press.
https://doi.org/10.1093/nar/gky079
chicago: Nikolic, Nela, Tobias Bergmiller, Alexandra Vandervelde, Tanino Albanese,
Lendert Gelens, and Isabella Moll. “Autoregulation of MazEF Expression Underlies
Growth Heterogeneity in Bacterial Populations.” Nucleic Acids Research.
Oxford University Press, 2018. https://doi.org/10.1093/nar/gky079.
ieee: N. Nikolic, T. Bergmiller, A. Vandervelde, T. Albanese, L. Gelens, and I.
Moll, “Autoregulation of mazEF expression underlies growth heterogeneity in bacterial
populations,” Nucleic Acids Research, vol. 46, no. 6. Oxford University
Press, pp. 2918–2931, 2018.
ista: Nikolic N, Bergmiller T, Vandervelde A, Albanese T, Gelens L, Moll I. 2018.
Autoregulation of mazEF expression underlies growth heterogeneity in bacterial
populations. Nucleic Acids Research. 46(6), 2918–2931.
mla: Nikolic, Nela, et al. “Autoregulation of MazEF Expression Underlies Growth
Heterogeneity in Bacterial Populations.” Nucleic Acids Research, vol. 46,
no. 6, Oxford University Press, 2018, pp. 2918–31, doi:10.1093/nar/gky079.
short: N. Nikolic, T. Bergmiller, A. Vandervelde, T. Albanese, L. Gelens, I. Moll,
Nucleic Acids Research 46 (2018) 2918–2931.
date_created: 2018-12-11T11:46:29Z
date_published: 2018-04-06T00:00:00Z
date_updated: 2024-02-21T13:44:45Z
day: '06'
ddc:
- '576'
department:
- _id: CaGu
doi: 10.1093/nar/gky079
external_id:
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date_updated: 2020-07-14T12:46:27Z
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file_name: IST-2018-971-v1+1_2018_Nikoloc_Autoregulation_of.pdf
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page: 2918-2931
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call_identifier: FWF
name: FWF Open Access Fund
publication: Nucleic Acids Research
publication_status: published
publisher: Oxford University Press
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related_material:
record:
- id: '5569'
relation: popular_science
status: public
scopus_import: '1'
status: public
title: Autoregulation of mazEF expression underlies growth heterogeneity in bacterial
populations
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: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 46
year: '2018'
...
---
_id: '541'
abstract:
- lang: eng
text: 'While we have good understanding of bacterial metabolism at the population
level, we know little about the metabolic behavior of individual cells: do single
cells in clonal populations sometimes specialize on different metabolic pathways?
Such metabolic specialization could be driven by stochastic gene expression and
could provide individual cells with growth benefits of specialization. We measured
the degree of phenotypic specialization in two parallel metabolic pathways, the
assimilation of glucose and arabinose. We grew Escherichia coli in chemostats,
and used isotope-labeled sugars in combination with nanometer-scale secondary
ion mass spectrometry and mathematical modeling to quantify sugar assimilation
at the single-cell level. We found large variation in metabolic activities between
single cells, both in absolute assimilation and in the degree to which individual
cells specialize in the assimilation of different sugars. Analysis of transcriptional
reporters indicated that this variation was at least partially based on cell-to-cell
variation in gene expression. Metabolic differences between cells in clonal populations
could potentially reduce metabolic incompatibilities between different pathways,
and increase the rate at which parallel reactions can be performed.'
article_number: e1007122
author:
- first_name: Nela
full_name: Nikolic, Nela
id: 42D9CABC-F248-11E8-B48F-1D18A9856A87
last_name: Nikolic
orcid: 0000-0001-9068-6090
- first_name: Frank
full_name: Schreiber, Frank
last_name: Schreiber
- first_name: Alma
full_name: Dal Co, Alma
last_name: Dal Co
- first_name: Daniel
full_name: Kiviet, Daniel
last_name: Kiviet
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Sten
full_name: Littmann, Sten
last_name: Littmann
- first_name: Marcel
full_name: Kuypers, Marcel
last_name: Kuypers
- first_name: Martin
full_name: Ackermann, Martin
last_name: Ackermann
citation:
ama: Nikolic N, Schreiber F, Dal Co A, et al. Cell-to-cell variation and specialization
in sugar metabolism in clonal bacterial populations. PLoS Genetics. 2017;13(12).
doi:10.1371/journal.pgen.1007122
apa: Nikolic, N., Schreiber, F., Dal Co, A., Kiviet, D., Bergmiller, T., Littmann,
S., … Ackermann, M. (2017). Cell-to-cell variation and specialization in sugar
metabolism in clonal bacterial populations. PLoS Genetics. Public Library
of Science. https://doi.org/10.1371/journal.pgen.1007122
chicago: Nikolic, Nela, Frank Schreiber, Alma Dal Co, Daniel Kiviet, Tobias Bergmiller,
Sten Littmann, Marcel Kuypers, and Martin Ackermann. “Cell-to-Cell Variation and
Specialization in Sugar Metabolism in Clonal Bacterial Populations.” PLoS Genetics.
Public Library of Science, 2017. https://doi.org/10.1371/journal.pgen.1007122.
ieee: N. Nikolic et al., “Cell-to-cell variation and specialization in sugar
metabolism in clonal bacterial populations,” PLoS Genetics, vol. 13, no.
12. Public Library of Science, 2017.
ista: Nikolic N, Schreiber F, Dal Co A, Kiviet D, Bergmiller T, Littmann S, Kuypers
M, Ackermann M. 2017. Cell-to-cell variation and specialization in sugar metabolism
in clonal bacterial populations. PLoS Genetics. 13(12), e1007122.
mla: Nikolic, Nela, et al. “Cell-to-Cell Variation and Specialization in Sugar Metabolism
in Clonal Bacterial Populations.” PLoS Genetics, vol. 13, no. 12, e1007122,
Public Library of Science, 2017, doi:10.1371/journal.pgen.1007122.
short: N. Nikolic, F. Schreiber, A. Dal Co, D. Kiviet, T. Bergmiller, S. Littmann,
M. Kuypers, M. Ackermann, PLoS Genetics 13 (2017).
date_created: 2018-12-11T11:47:04Z
date_published: 2017-12-18T00:00:00Z
date_updated: 2023-02-23T14:10:34Z
day: '18'
ddc:
- '576'
- '579'
department:
- _id: CaGu
doi: 10.1371/journal.pgen.1007122
ec_funded: 1
file:
- access_level: open_access
checksum: 22426d9382f21554bad5fa5967afcfd0
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:14:35Z
date_updated: 2020-07-14T12:46:46Z
file_id: '5088'
file_name: IST-2018-959-v1+1_2017_Nikolic_Cell-to-cell.pdf
file_size: 1308475
relation: main_file
file_date_updated: 2020-07-14T12:46:46Z
has_accepted_license: '1'
intvolume: ' 13'
issue: '12'
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
publication: PLoS Genetics
publication_identifier:
issn:
- '15537390'
publication_status: published
publisher: Public Library of Science
publist_id: '7275'
pubrep_id: '959'
quality_controlled: '1'
related_material:
record:
- id: '9844'
relation: research_data
status: public
- id: '9845'
relation: research_data
status: public
- id: '9846'
relation: research_data
status: public
scopus_import: 1
status: public
title: Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial
populations
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: 13
year: '2017'
...
---
_id: '624'
abstract:
- lang: eng
text: Bacteria adapt to adverse environmental conditions by altering gene expression
patterns. Recently, a novel stress adaptation mechanism has been described that
allows Escherichia coli to alter gene expression at the post-transcriptional level.
The key player in this regulatory pathway is the endoribonuclease MazF, the toxin
component of the toxin-antitoxin module mazEF that is triggered by various stressful
conditions. In general, MazF degrades the majority of transcripts by cleaving
at ACA sites, which results in the retardation of bacterial growth. Furthermore,
MazF can process a small subset of mRNAs and render them leaderless by removing
their ribosome binding site. MazF concomitantly modifies ribosomes, making them
selective for the translation of leaderless mRNAs. In this study, we employed
fluorescent reporter-systems to investigate mazEF expression during stressful
conditions, and to infer consequences of the mRNA processing mediated by MazF
on gene expression at the single-cell level. Our results suggest that mazEF transcription
is maintained at low levels in single cells encountering adverse conditions, such
as antibiotic stress or amino acid starvation. Moreover, using the grcA mRNA as
a model for MazF-mediated mRNA processing, we found that MazF activation promotes
heterogeneity in the grcA reporter expression, resulting in a subpopulation of
cells with increased levels of GrcA reporter protein.
acknowledgement: 'Austrian Science Fund (FWF): M1697, P22249; Swiss National Science
Foundation (SNF): 145706; European Commission;FWF Special Research Program: RNA-REG
F43'
article_number: '3830'
author:
- first_name: Nela
full_name: Nikolic, Nela
id: 42D9CABC-F248-11E8-B48F-1D18A9856A87
last_name: Nikolic
orcid: 0000-0001-9068-6090
- first_name: Zrinka
full_name: Didara, Zrinka
last_name: Didara
- first_name: Isabella
full_name: Moll, Isabella
last_name: Moll
citation:
ama: Nikolic N, Didara Z, Moll I. MazF activation promotes translational heterogeneity
of the grcA mRNA in Escherichia coli populations. PeerJ. 2017;2017(9).
doi:10.7717/peerj.3830
apa: Nikolic, N., Didara, Z., & Moll, I. (2017). MazF activation promotes translational
heterogeneity of the grcA mRNA in Escherichia coli populations. PeerJ.
PeerJ. https://doi.org/10.7717/peerj.3830
chicago: Nikolic, Nela, Zrinka Didara, and Isabella Moll. “MazF Activation Promotes
Translational Heterogeneity of the GrcA MRNA in Escherichia Coli Populations.”
PeerJ. PeerJ, 2017. https://doi.org/10.7717/peerj.3830.
ieee: N. Nikolic, Z. Didara, and I. Moll, “MazF activation promotes translational
heterogeneity of the grcA mRNA in Escherichia coli populations,” PeerJ,
vol. 2017, no. 9. PeerJ, 2017.
ista: Nikolic N, Didara Z, Moll I. 2017. MazF activation promotes translational
heterogeneity of the grcA mRNA in Escherichia coli populations. PeerJ. 2017(9),
3830.
mla: Nikolic, Nela, et al. “MazF Activation Promotes Translational Heterogeneity
of the GrcA MRNA in Escherichia Coli Populations.” PeerJ, vol. 2017, no.
9, 3830, PeerJ, 2017, doi:10.7717/peerj.3830.
short: N. Nikolic, Z. Didara, I. Moll, PeerJ 2017 (2017).
date_created: 2018-12-11T11:47:33Z
date_published: 2017-09-21T00:00:00Z
date_updated: 2021-01-12T08:06:48Z
day: '21'
ddc:
- '579'
department:
- _id: CaGu
doi: 10.7717/peerj.3830
file:
- access_level: open_access
checksum: 3d79ae6b6eabc90b0eaaed82ff3493b0
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:11:51Z
date_updated: 2020-07-14T12:47:24Z
file_id: '4908'
file_name: IST-2017-909-v1+1_peerj-3830.pdf
file_size: 682064
relation: main_file
file_date_updated: 2020-07-14T12:47:24Z
has_accepted_license: '1'
intvolume: ' 2017'
issue: '9'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
publication: PeerJ
publication_identifier:
issn:
- '21678359'
publication_status: published
publisher: PeerJ
publist_id: '7172'
pubrep_id: '909'
quality_controlled: '1'
scopus_import: 1
status: public
title: MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia
coli populations
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: 2017
year: '2017'
...
---
_id: '9844'
article_processing_charge: No
author:
- first_name: Nela
full_name: Nikolic, Nela
id: 42D9CABC-F248-11E8-B48F-1D18A9856A87
last_name: Nikolic
orcid: 0000-0001-9068-6090
- first_name: Frank
full_name: Schreiber, Frank
last_name: Schreiber
- first_name: Alma
full_name: Dal Co, Alma
last_name: Dal Co
- first_name: Daniel
full_name: Kiviet, Daniel
last_name: Kiviet
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Sten
full_name: Littmann, Sten
last_name: Littmann
- first_name: Marcel
full_name: Kuypers, Marcel
last_name: Kuypers
- first_name: Martin
full_name: Ackermann, Martin
last_name: Ackermann
citation:
ama: Nikolic N, Schreiber F, Dal Co A, et al. Source data for figures and tables.
2017. doi:10.1371/journal.pgen.1007122.s018
apa: Nikolic, N., Schreiber, F., Dal Co, A., Kiviet, D., Bergmiller, T., Littmann,
S., … Ackermann, M. (2017). Source data for figures and tables. Public Library
of Science. https://doi.org/10.1371/journal.pgen.1007122.s018
chicago: Nikolic, Nela, Frank Schreiber, Alma Dal Co, Daniel Kiviet, Tobias Bergmiller,
Sten Littmann, Marcel Kuypers, and Martin Ackermann. “Source Data for Figures
and Tables.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pgen.1007122.s018.
ieee: N. Nikolic et al., “Source data for figures and tables.” Public Library
of Science, 2017.
ista: Nikolic N, Schreiber F, Dal Co A, Kiviet D, Bergmiller T, Littmann S, Kuypers
M, Ackermann M. 2017. Source data for figures and tables, Public Library of Science,
10.1371/journal.pgen.1007122.s018.
mla: Nikolic, Nela, et al. Source Data for Figures and Tables. Public Library
of Science, 2017, doi:10.1371/journal.pgen.1007122.s018.
short: N. Nikolic, F. Schreiber, A. Dal Co, D. Kiviet, T. Bergmiller, S. Littmann,
M. Kuypers, M. Ackermann, (2017).
date_created: 2021-08-09T13:27:16Z
date_published: 2017-12-18T00:00:00Z
date_updated: 2023-02-23T12:25:04Z
day: '18'
department:
- _id: CaGu
doi: 10.1371/journal.pgen.1007122.s018
month: '12'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '541'
relation: used_in_publication
status: public
status: public
title: Source data for figures and tables
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2017'
...
---
_id: '9845'
abstract:
- lang: eng
text: "Estimates of 13 C-arabinose and 2 H-glucose uptake from the fractions of
heavy isotopes measured\tin single cells"
article_processing_charge: No
author:
- first_name: Nela
full_name: Nikolic, Nela
id: 42D9CABC-F248-11E8-B48F-1D18A9856A87
last_name: Nikolic
orcid: 0000-0001-9068-6090
- first_name: Frank
full_name: Schreiber, Frank
last_name: Schreiber
- first_name: Alma
full_name: Dal Co, Alma
last_name: Dal Co
- first_name: Daniel
full_name: Kiviet, Daniel
last_name: Kiviet
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Sten
full_name: Littmann, Sten
last_name: Littmann
- first_name: Marcel
full_name: Kuypers, Marcel
last_name: Kuypers
- first_name: Martin
full_name: Ackermann, Martin
last_name: Ackermann
citation:
ama: Nikolic N, Schreiber F, Dal Co A, et al. Mathematical model. 2017. doi:10.1371/journal.pgen.1007122.s017
apa: Nikolic, N., Schreiber, F., Dal Co, A., Kiviet, D., Bergmiller, T., Littmann,
S., … Ackermann, M. (2017). Mathematical model. Public Library of Science. https://doi.org/10.1371/journal.pgen.1007122.s017
chicago: Nikolic, Nela, Frank Schreiber, Alma Dal Co, Daniel Kiviet, Tobias Bergmiller,
Sten Littmann, Marcel Kuypers, and Martin Ackermann. “Mathematical Model.” Public
Library of Science, 2017. https://doi.org/10.1371/journal.pgen.1007122.s017.
ieee: N. Nikolic et al., “Mathematical model.” Public Library of Science,
2017.
ista: Nikolic N, Schreiber F, Dal Co A, Kiviet D, Bergmiller T, Littmann S, Kuypers
M, Ackermann M. 2017. Mathematical model, Public Library of Science, 10.1371/journal.pgen.1007122.s017.
mla: Nikolic, Nela, et al. Mathematical Model. Public Library of Science,
2017, doi:10.1371/journal.pgen.1007122.s017.
short: N. Nikolic, F. Schreiber, A. Dal Co, D. Kiviet, T. Bergmiller, S. Littmann,
M. Kuypers, M. Ackermann, (2017).
date_created: 2021-08-09T13:31:51Z
date_published: 2017-12-18T00:00:00Z
date_updated: 2023-02-23T12:25:04Z
day: '18'
department:
- _id: CaGu
doi: 10.1371/journal.pgen.1007122.s017
month: '12'
oa_version: None
publisher: Public Library of Science
related_material:
record:
- id: '541'
relation: used_in_publication
status: public
status: public
title: Mathematical model
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2017'
...
---
_id: '9846'
article_processing_charge: No
author:
- first_name: Nela
full_name: Nikolic, Nela
id: 42D9CABC-F248-11E8-B48F-1D18A9856A87
last_name: Nikolic
orcid: 0000-0001-9068-6090
- first_name: Frank
full_name: Schreiber, Frank
last_name: Schreiber
- first_name: Alma
full_name: Dal Co, Alma
last_name: Dal Co
- first_name: Daniel
full_name: Kiviet, Daniel
last_name: Kiviet
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Sten
full_name: Littmann, Sten
last_name: Littmann
- first_name: Marcel
full_name: Kuypers, Marcel
last_name: Kuypers
- first_name: Martin
full_name: Ackermann, Martin
last_name: Ackermann
citation:
ama: Nikolic N, Schreiber F, Dal Co A, et al. Supplementary methods. 2017. doi:10.1371/journal.pgen.1007122.s016
apa: Nikolic, N., Schreiber, F., Dal Co, A., Kiviet, D., Bergmiller, T., Littmann,
S., … Ackermann, M. (2017). Supplementary methods. Public Library of Science.
https://doi.org/10.1371/journal.pgen.1007122.s016
chicago: Nikolic, Nela, Frank Schreiber, Alma Dal Co, Daniel Kiviet, Tobias Bergmiller,
Sten Littmann, Marcel Kuypers, and Martin Ackermann. “Supplementary Methods.”
Public Library of Science, 2017. https://doi.org/10.1371/journal.pgen.1007122.s016.
ieee: N. Nikolic et al., “Supplementary methods.” Public Library of Science,
2017.
ista: Nikolic N, Schreiber F, Dal Co A, Kiviet D, Bergmiller T, Littmann S, Kuypers
M, Ackermann M. 2017. Supplementary methods, Public Library of Science, 10.1371/journal.pgen.1007122.s016.
mla: Nikolic, Nela, et al. Supplementary Methods. Public Library of Science,
2017, doi:10.1371/journal.pgen.1007122.s016.
short: N. Nikolic, F. Schreiber, A. Dal Co, D. Kiviet, T. Bergmiller, S. Littmann,
M. Kuypers, M. Ackermann, (2017).
date_created: 2021-08-09T13:35:17Z
date_published: 2017-12-18T00:00:00Z
date_updated: 2023-02-23T12:25:04Z
day: '18'
department:
- _id: CaGu
doi: 10.1371/journal.pgen.1007122.s016
month: '12'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '541'
relation: used_in_publication
status: public
status: public
title: Supplementary methods
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2017'
...