DNA nanomachines: monitoring molecular encounter dynamics in live cell membranes

DNA nanomachines: monitoring molecular encounter dynamics in live cell membranes The cell membrane features a variety of heterogeneous and dynamic compartments to regulate cell structure and function. These compartments are generally classified into a relatively packed, lipid-ordered (Lo) domain (10-200 nm) enriched in saturated lipids and cholesterol, and a more fluid, liquid-disordered (Ld) domain comprising mainly unsaturated lipids [1]. According to the lipid raft theory, Lo domains, which selectively recruit specific lipids and proteins, serve as critical platforms for signal transduction and membrane protein trafficking [2]. Therefore, resolving the interplay and dynamics of lipids and proteins on the plasma membrane is of great importance to unveil the properties and biological relevance of membrane domains. Despite accumulating knowledge from in vitro assays, the organization and dynamics of membrane domains in living cells are still elusive. Efforts have been made to use advanced microscopic techniques such as single-molecule tracking (SMT), super-resolution fluorescence imaging and Förster resonance energy transfer (FRET) for live-cell investigations [3]. For example, the application of SMT to evaluate the oligomerization, transient interaction, domain incorporation and diffusion of membrane components has been demonstrated. However, the limitations of these methods include complex instrumentation and operation, inefficient time resolution for transient interaction at the μs level and/or inability of simultaneously monitoring of the entire plasma membrane [4]. In recent work by the Tan group, a simple and elegant method was developed to probe the dynamics of membrane lipids and proteins in living cells. This was achieved by taking advantage of emerging DNA nanomachine technology. As shown in Fig. 1, they designed a DNA nanomachine operated with five ssDNA probes: two anchor strands (S1, S2) that linked to two target membrane components (lipids in this case) and labeled with a quencher in one strand (S1), one walker strand (W) labeled with a fluorophore, one block strand (B) and one initiator strand (I). In the absence of I, S1 and S2 hybridized with B and W, respectively, at different locations on the cell surface; thus, the cell was fluorescent. Running of the nanomachine was initiated with the addition of strand I, which removed strand B from strand S1. Therefore, when the two target components encountered, strand W was translocated from S2 to S1 for W/S1 hybridization through a toehold-mediated DNA strand displacement, resulting in the quenching of fluorescence. In this way, the transient membrane encounter events were transduced to the cumulative fluorescence signal change, which was easily measured by the commonly accessible flow cytometry or fluorescence microscopy [5]. Figure 1. View largeDownload slide Schematic illustration of the DNA nanomachine operation on live-cell membrane. After the addition of the initiator (I) strand to remove the block (B) strand from the anchor site S1, the locomotion of the DNA walker strand (W) from anchor site S2 to S1 is monitored by detecting the fluorescence signal decrease. Thus the collision of the two membrane components respectively conjugated with S1 and S2 is probed (from [5]). Figure 1. View largeDownload slide Schematic illustration of the DNA nanomachine operation on live-cell membrane. After the addition of the initiator (I) strand to remove the block (B) strand from the anchor site S1, the locomotion of the DNA walker strand (W) from anchor site S2 to S1 is monitored by detecting the fluorescence signal decrease. Thus the collision of the two membrane components respectively conjugated with S1 and S2 is probed (from [5]). The authors used this method to study three typical lipids on the plasma membrane of Ramos cells: Lo lipid diacyllipids (L), Ld lipid tocopherols (T) and cholesterols (C). Their encounter rates, encounter preference and percentage of diffusion areas across the cell membrane have been calculated. The results suppor-ted the lipid raft theory that the plasma membrane is heterogeneous and the same lipids tend to confine in the same type of lipid domain. In addition, after coupling the protein-specific aptamers to the DNA nanomachine probes, they applied the same method to investigate the interaction of membrane proteins. The strategy developed by the Tan group demonstrates a novel and practical way to study dynamic interactions of membrane components. Although it needs to be considered whether the diffusion and encounter of native lipids or proteins are affected by the DNA strand conjugation and strand displacement efficiency, exploring the new DNA nanomachines to live-cell investigation is of great interest. Future work would be expected to correlate the membrane encounter dynamics with important cellular processes, such as membrane trafficking, cell signaling and cell polarization, to further our understanding of membrane functions, especially their differences in healthy and diseased states. REFERENCES 1. Sezgin E, Levental I, Mayor S et al.   Nat Rev Mol Cell Biol  2017; 18: 361– 74. CrossRef Search ADS PubMed  2. Honigmann A, Mueller V, Ta H et al.   Nat Commun  2014; 5: 5412. CrossRef Search ADS PubMed  3. Xia T, Li N, Fang XH. Annu Rev Phys Chem  2013; 64: 459– 80. CrossRef Search ADS PubMed  4. Sezgin E, Schwille P. Cold Spring Harb Perspect Biol  2011; 3: a009803. CrossRef Search ADS PubMed  5. You M, Lyu Y, Han D et al.   Nat Nanotechnol  2017; 12: 453– 9. CrossRef Search ADS PubMed  © The Author(s) 2017. Published by Oxford University Press on behalf of China Science Publishing & Media Ltd. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png National Science Review Oxford University Press

DNA nanomachines: monitoring molecular encounter dynamics in live cell membranes

National Science Review , Volume Advance Article (3) – Aug 11, 2017

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Publisher
Oxford University Press
Copyright
© The Author(s) 2017. Published by Oxford University Press on behalf of China Science Publishing & Media Ltd.
ISSN
2095-5138
eISSN
2053-714X
D.O.I.
10.1093/nsr/nwx091
Publisher site
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Abstract

The cell membrane features a variety of heterogeneous and dynamic compartments to regulate cell structure and function. These compartments are generally classified into a relatively packed, lipid-ordered (Lo) domain (10-200 nm) enriched in saturated lipids and cholesterol, and a more fluid, liquid-disordered (Ld) domain comprising mainly unsaturated lipids [1]. According to the lipid raft theory, Lo domains, which selectively recruit specific lipids and proteins, serve as critical platforms for signal transduction and membrane protein trafficking [2]. Therefore, resolving the interplay and dynamics of lipids and proteins on the plasma membrane is of great importance to unveil the properties and biological relevance of membrane domains. Despite accumulating knowledge from in vitro assays, the organization and dynamics of membrane domains in living cells are still elusive. Efforts have been made to use advanced microscopic techniques such as single-molecule tracking (SMT), super-resolution fluorescence imaging and Förster resonance energy transfer (FRET) for live-cell investigations [3]. For example, the application of SMT to evaluate the oligomerization, transient interaction, domain incorporation and diffusion of membrane components has been demonstrated. However, the limitations of these methods include complex instrumentation and operation, inefficient time resolution for transient interaction at the μs level and/or inability of simultaneously monitoring of the entire plasma membrane [4]. In recent work by the Tan group, a simple and elegant method was developed to probe the dynamics of membrane lipids and proteins in living cells. This was achieved by taking advantage of emerging DNA nanomachine technology. As shown in Fig. 1, they designed a DNA nanomachine operated with five ssDNA probes: two anchor strands (S1, S2) that linked to two target membrane components (lipids in this case) and labeled with a quencher in one strand (S1), one walker strand (W) labeled with a fluorophore, one block strand (B) and one initiator strand (I). In the absence of I, S1 and S2 hybridized with B and W, respectively, at different locations on the cell surface; thus, the cell was fluorescent. Running of the nanomachine was initiated with the addition of strand I, which removed strand B from strand S1. Therefore, when the two target components encountered, strand W was translocated from S2 to S1 for W/S1 hybridization through a toehold-mediated DNA strand displacement, resulting in the quenching of fluorescence. In this way, the transient membrane encounter events were transduced to the cumulative fluorescence signal change, which was easily measured by the commonly accessible flow cytometry or fluorescence microscopy [5]. Figure 1. View largeDownload slide Schematic illustration of the DNA nanomachine operation on live-cell membrane. After the addition of the initiator (I) strand to remove the block (B) strand from the anchor site S1, the locomotion of the DNA walker strand (W) from anchor site S2 to S1 is monitored by detecting the fluorescence signal decrease. Thus the collision of the two membrane components respectively conjugated with S1 and S2 is probed (from [5]). Figure 1. View largeDownload slide Schematic illustration of the DNA nanomachine operation on live-cell membrane. After the addition of the initiator (I) strand to remove the block (B) strand from the anchor site S1, the locomotion of the DNA walker strand (W) from anchor site S2 to S1 is monitored by detecting the fluorescence signal decrease. Thus the collision of the two membrane components respectively conjugated with S1 and S2 is probed (from [5]). The authors used this method to study three typical lipids on the plasma membrane of Ramos cells: Lo lipid diacyllipids (L), Ld lipid tocopherols (T) and cholesterols (C). Their encounter rates, encounter preference and percentage of diffusion areas across the cell membrane have been calculated. The results suppor-ted the lipid raft theory that the plasma membrane is heterogeneous and the same lipids tend to confine in the same type of lipid domain. In addition, after coupling the protein-specific aptamers to the DNA nanomachine probes, they applied the same method to investigate the interaction of membrane proteins. The strategy developed by the Tan group demonstrates a novel and practical way to study dynamic interactions of membrane components. Although it needs to be considered whether the diffusion and encounter of native lipids or proteins are affected by the DNA strand conjugation and strand displacement efficiency, exploring the new DNA nanomachines to live-cell investigation is of great interest. Future work would be expected to correlate the membrane encounter dynamics with important cellular processes, such as membrane trafficking, cell signaling and cell polarization, to further our understanding of membrane functions, especially their differences in healthy and diseased states. REFERENCES 1. Sezgin E, Levental I, Mayor S et al.   Nat Rev Mol Cell Biol  2017; 18: 361– 74. CrossRef Search ADS PubMed  2. Honigmann A, Mueller V, Ta H et al.   Nat Commun  2014; 5: 5412. CrossRef Search ADS PubMed  3. Xia T, Li N, Fang XH. Annu Rev Phys Chem  2013; 64: 459– 80. CrossRef Search ADS PubMed  4. Sezgin E, Schwille P. Cold Spring Harb Perspect Biol  2011; 3: a009803. CrossRef Search ADS PubMed  5. You M, Lyu Y, Han D et al.   Nat Nanotechnol  2017; 12: 453– 9. CrossRef Search ADS PubMed  © The Author(s) 2017. Published by Oxford University Press on behalf of China Science Publishing & Media Ltd. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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National Science ReviewOxford University Press

Published: Aug 11, 2017

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