Lineage tracking for probing heritable phenotypes at single-cell resolution

Determining the phenotype and genotype of single cells is central to understand microbial evolution. DNA sequencing technologies allow the detection of mutants at high resolution, but similar approaches for phenotypic analyses are still lacking. We show that a drop-based millifluidic system enables the detection of heritable phenotypic changes in evolving bacterial populations. At time intervals, cells were sampled and individually compartmentalized in 100 nL drops. Growth through 15 generations was monitored using a fluorescent protein reporter. Amplification of heritable changes-via growth-over multiple generations yields phenotypically distinct clusters reflecting variation relevant for evolution. To demonstrate the utility of this approach, we follow the evolution of Escherichia coli populations during 30 days of starvation. Phenotypic diversity was observed to rapidly increase upon starvation with the emergence of heritable phenotypes. Mutations corresponding to each phenotypic class were identified by DNA sequencing. This scalable lineage-tracking technology opens the door to large-scale phenotyping methods with special utility for microbiology and microbial population biology.

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Main Authors: Cottinet, Denis, Condamine, Florence, Bremond, Nicolas, Griffiths, Andrew D., Rainey, Paul B., de Visser, Arjan, Baudry, Jean, Bibette, Jérôme
Format: Article/Letter to editor biblioteca
Language:English
Subjects:Life Science,
Online Access:https://research.wur.nl/en/publications/lineage-tracking-for-probing-heritable-phenotypes-at-single-cell-
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spelling dig-wur-nl-wurpubs-5063542024-09-23 Cottinet, Denis Condamine, Florence Bremond, Nicolas Griffiths, Andrew D. Rainey, Paul B. de Visser, Arjan Baudry, Jean Bibette, Jérôme Article/Letter to editor PLoS ONE 11 (2016) 4 ISSN: 1932-6203 Lineage tracking for probing heritable phenotypes at single-cell resolution 2016 Determining the phenotype and genotype of single cells is central to understand microbial evolution. DNA sequencing technologies allow the detection of mutants at high resolution, but similar approaches for phenotypic analyses are still lacking. We show that a drop-based millifluidic system enables the detection of heritable phenotypic changes in evolving bacterial populations. At time intervals, cells were sampled and individually compartmentalized in 100 nL drops. Growth through 15 generations was monitored using a fluorescent protein reporter. Amplification of heritable changes-via growth-over multiple generations yields phenotypically distinct clusters reflecting variation relevant for evolution. To demonstrate the utility of this approach, we follow the evolution of Escherichia coli populations during 30 days of starvation. Phenotypic diversity was observed to rapidly increase upon starvation with the emergence of heritable phenotypes. Mutations corresponding to each phenotypic class were identified by DNA sequencing. This scalable lineage-tracking technology opens the door to large-scale phenotyping methods with special utility for microbiology and microbial population biology. en application/pdf https://research.wur.nl/en/publications/lineage-tracking-for-probing-heritable-phenotypes-at-single-cell- 10.1371/journal.pone.0152395 https://edepot.wur.nl/387283 Life Science https://creativecommons.org/licenses/by/4.0/ Wageningen University & Research
institution WUR NL
collection DSpace
country Países bajos
countrycode NL
component Bibliográfico
access En linea
databasecode dig-wur-nl
tag biblioteca
region Europa del Oeste
libraryname WUR Library Netherlands
language English
topic Life Science
Life Science
spellingShingle Life Science
Life Science
Cottinet, Denis
Condamine, Florence
Bremond, Nicolas
Griffiths, Andrew D.
Rainey, Paul B.
de Visser, Arjan
Baudry, Jean
Bibette, Jérôme
Lineage tracking for probing heritable phenotypes at single-cell resolution
description Determining the phenotype and genotype of single cells is central to understand microbial evolution. DNA sequencing technologies allow the detection of mutants at high resolution, but similar approaches for phenotypic analyses are still lacking. We show that a drop-based millifluidic system enables the detection of heritable phenotypic changes in evolving bacterial populations. At time intervals, cells were sampled and individually compartmentalized in 100 nL drops. Growth through 15 generations was monitored using a fluorescent protein reporter. Amplification of heritable changes-via growth-over multiple generations yields phenotypically distinct clusters reflecting variation relevant for evolution. To demonstrate the utility of this approach, we follow the evolution of Escherichia coli populations during 30 days of starvation. Phenotypic diversity was observed to rapidly increase upon starvation with the emergence of heritable phenotypes. Mutations corresponding to each phenotypic class were identified by DNA sequencing. This scalable lineage-tracking technology opens the door to large-scale phenotyping methods with special utility for microbiology and microbial population biology.
format Article/Letter to editor
topic_facet Life Science
author Cottinet, Denis
Condamine, Florence
Bremond, Nicolas
Griffiths, Andrew D.
Rainey, Paul B.
de Visser, Arjan
Baudry, Jean
Bibette, Jérôme
author_facet Cottinet, Denis
Condamine, Florence
Bremond, Nicolas
Griffiths, Andrew D.
Rainey, Paul B.
de Visser, Arjan
Baudry, Jean
Bibette, Jérôme
author_sort Cottinet, Denis
title Lineage tracking for probing heritable phenotypes at single-cell resolution
title_short Lineage tracking for probing heritable phenotypes at single-cell resolution
title_full Lineage tracking for probing heritable phenotypes at single-cell resolution
title_fullStr Lineage tracking for probing heritable phenotypes at single-cell resolution
title_full_unstemmed Lineage tracking for probing heritable phenotypes at single-cell resolution
title_sort lineage tracking for probing heritable phenotypes at single-cell resolution
url https://research.wur.nl/en/publications/lineage-tracking-for-probing-heritable-phenotypes-at-single-cell-
work_keys_str_mv AT cottinetdenis lineagetrackingforprobingheritablephenotypesatsinglecellresolution
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