A 3D-printed flow-cell for on-grid purification of electron microscopy samples directly from lysate
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Published version
Author(s)
Type
Journal Article
Abstract
While recent advances in cryo-EM, coupled with single particle analysis, have the
potential to allow structure determination in a near-native state from vanishingly few individual
particles, this vision has yet to be realised in practise. Requirements for particle numbers that
currently far exceed the theoretical lower limits, challenges with the practicalities of achieving
high concentrations for difficult-to-produce samples, and inadequate sample-dependent imaging
conditions, all result in significant bottlenecks preventing routine structure determination using
cryo-EM. Therefore, considerable efforts are being made to circumvent these bottlenecks by
developing affinity purification of samples on-grid; at once obviating the need to produce large
amounts of protein, as well as more directly controlling the variable, and sample-dependent,
process of grid preparation.
In this proof-of-concept study, we demonstrate a further practical step towards this
paradigm, developing a 3D-printable flow-cell device to allow on-grid affinity purification from
raw inputs such as whole cell lysates, using graphene oxide-based affinity grids. Our flow-cell
device can be interfaced directly with routinely-used laboratory equipment such as liquid
chromatographs, or peristaltic pumps, fitted with standard chromatographic (1/16”) connectors,
and can be used to allow binding of samples to affinity grids in a controlled environment prior
to the extensive washing required to remove impurities. Furthermore, by designing a device
which can be 3D printed and coupled to routinely used laboratory equipment, we hope to
increase the accessibility of the techniques presented herein to researchers working towards
single-particle macromolecular structures.
potential to allow structure determination in a near-native state from vanishingly few individual
particles, this vision has yet to be realised in practise. Requirements for particle numbers that
currently far exceed the theoretical lower limits, challenges with the practicalities of achieving
high concentrations for difficult-to-produce samples, and inadequate sample-dependent imaging
conditions, all result in significant bottlenecks preventing routine structure determination using
cryo-EM. Therefore, considerable efforts are being made to circumvent these bottlenecks by
developing affinity purification of samples on-grid; at once obviating the need to produce large
amounts of protein, as well as more directly controlling the variable, and sample-dependent,
process of grid preparation.
In this proof-of-concept study, we demonstrate a further practical step towards this
paradigm, developing a 3D-printable flow-cell device to allow on-grid affinity purification from
raw inputs such as whole cell lysates, using graphene oxide-based affinity grids. Our flow-cell
device can be interfaced directly with routinely-used laboratory equipment such as liquid
chromatographs, or peristaltic pumps, fitted with standard chromatographic (1/16”) connectors,
and can be used to allow binding of samples to affinity grids in a controlled environment prior
to the extensive washing required to remove impurities. Furthermore, by designing a device
which can be 3D printed and coupled to routinely used laboratory equipment, we hope to
increase the accessibility of the techniques presented herein to researchers working towards
single-particle macromolecular structures.
Date Issued
2023-09
Date Acceptance
2023-07-10
Citation
Journal of Structural Biology, 2023, 215 (3), pp.1-12
ISSN
1047-8477
Publisher
Elsevier
Start Page
1
End Page
12
Journal / Book Title
Journal of Structural Biology
Volume
215
Issue
3
Copyright Statement
© 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
https://www.sciencedirect.com/science/article/pii/S104784772300062X
Publication Status
Published
Article Number
107999
Date Publish Online
2023-07-13