High-reynolds microfluidic sorting of large yeast populations
High-reynolds microfluidic sorting of large yeast populations
Microfluidic sorting offers a unique ability to isolate large numbers of cells for bulk proteomic or metabolomics studies but is currently limited by low throughput and persistent clogging at low flow rates. Recently we uncovered the physical principles governing the inertial focusing of particles in high-Reynolds numbers. Here, we superimpose high Reynolds inertial focusing on Dean vortices, to rapidly isolate large quantities of young and adult yeast from mixed populations at a rate of 107 cells/min/channel. Using a new algorithm to rapidly quantify budding scars in isolated yeast populations and system-wide proteomic analysis, we demonstrate that protein quality control and expression of established yeast aging markers such as CalM, RPL5, and SAM1 may change after the very first replication events, rather than later in the aging process as previously thought. Our technique enables the large-scale isolation of microorganisms based on minute differences in size (±1.5 μm), a feat unmatched by other technologies.
Equipment Design, Lab-On-A-Chip Devices, Microfluidics/instrumentation, Proteomics, Saccharomyces cerevisiae/growth & development
13739
Keinan, Eliezer
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Abraham, Ayelet Chen
9d7bdc49-a883-463d-acce-8635fa88e8b1
Cohen, Aaron
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Alexandrov, Alexander I
d60f7f17-553b-4cfa-a6ce-f755868172d7
Mintz, Reshef
0892affd-03cc-48ff-924f-9627f6386137
Cohen, Merav
6a277760-27cd-4f0c-b82a-4090524e6a1e
Reichmann, Dana
0b6b55e4-f979-42c7-8de4-1c13c61df633
Kaganovich, Daniel
ebb13f4e-e925-4aef-88e7-ddc25ef52d8f
Nahmias, Yaakov
fadbfc9b-3ac4-4380-a10f-078bd616a4d4
13 September 2018
Keinan, Eliezer
f87641d4-61dc-492a-bf34-86684ad9f327
Abraham, Ayelet Chen
9d7bdc49-a883-463d-acce-8635fa88e8b1
Cohen, Aaron
3de58597-a4ce-4813-9c07-9280a57d5dc5
Alexandrov, Alexander I
d60f7f17-553b-4cfa-a6ce-f755868172d7
Mintz, Reshef
0892affd-03cc-48ff-924f-9627f6386137
Cohen, Merav
6a277760-27cd-4f0c-b82a-4090524e6a1e
Reichmann, Dana
0b6b55e4-f979-42c7-8de4-1c13c61df633
Kaganovich, Daniel
ebb13f4e-e925-4aef-88e7-ddc25ef52d8f
Nahmias, Yaakov
fadbfc9b-3ac4-4380-a10f-078bd616a4d4
Keinan, Eliezer, Abraham, Ayelet Chen, Cohen, Aaron, Alexandrov, Alexander I, Mintz, Reshef, Cohen, Merav, Reichmann, Dana, Kaganovich, Daniel and Nahmias, Yaakov
(2018)
High-reynolds microfluidic sorting of large yeast populations.
Scientific Reports, 8 (1), .
(doi:10.1038/s41598-018-31726-6).
Abstract
Microfluidic sorting offers a unique ability to isolate large numbers of cells for bulk proteomic or metabolomics studies but is currently limited by low throughput and persistent clogging at low flow rates. Recently we uncovered the physical principles governing the inertial focusing of particles in high-Reynolds numbers. Here, we superimpose high Reynolds inertial focusing on Dean vortices, to rapidly isolate large quantities of young and adult yeast from mixed populations at a rate of 107 cells/min/channel. Using a new algorithm to rapidly quantify budding scars in isolated yeast populations and system-wide proteomic analysis, we demonstrate that protein quality control and expression of established yeast aging markers such as CalM, RPL5, and SAM1 may change after the very first replication events, rather than later in the aging process as previously thought. Our technique enables the large-scale isolation of microorganisms based on minute differences in size (±1.5 μm), a feat unmatched by other technologies.
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Published date: 13 September 2018
Keywords:
Equipment Design, Lab-On-A-Chip Devices, Microfluidics/instrumentation, Proteomics, Saccharomyces cerevisiae/growth & development
Identifiers
Local EPrints ID: 482096
URI: http://eprints.soton.ac.uk/id/eprint/482096
ISSN: 2045-2322
PURE UUID: 89dc123c-f977-42d2-b823-206b230fac15
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Date deposited: 19 Sep 2023 16:35
Last modified: 17 Mar 2024 04:17
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Contributors
Author:
Eliezer Keinan
Author:
Ayelet Chen Abraham
Author:
Aaron Cohen
Author:
Alexander I Alexandrov
Author:
Reshef Mintz
Author:
Merav Cohen
Author:
Dana Reichmann
Author:
Daniel Kaganovich
Author:
Yaakov Nahmias
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