Destructive extraction of phospholipids from Escherichia coli membranes by graphene nanosheets

Journal name:
Nature Nanotechnology
Volume:
8,
Pages:
594–601
Year published:
DOI:
doi:10.1038/nnano.2013.125
Received
Accepted
Published online
Corrected online

Abstract

Understanding how nanomaterials interact with cell membranes is related to how they cause cytotoxicity and is therefore critical for designing safer biomedical applications. Recently, graphene (a two-dimensional nanomaterial) was shown to have antibacterial activity on Escherichia coli, but its underlying molecular mechanisms remain unknown. Here we show experimentally and theoretically that pristine graphene and graphene oxide nanosheets can induce the degradation of the inner and outer cell membranes of Escherichia coli, and reduce their viability. Transmission electron microscopy shows three rough stages, and molecular dynamics simulations reveal the atomic details of the process. Graphene nanosheets can penetrate into and extract large amounts of phospholipids from the cell membranes because of the strong dispersion interactions between graphene and lipid molecules. This destructive extraction offers a novel mechanism for the molecular basis of graphene's cytotoxicity and antibacterial activity.

At a glance

Figures

  1. Morphology of E. coli exposed to graphene oxide nanosheets.
    Figure 1: Morphology of E. coli exposed to graphene oxide nanosheets.

    TEM images showing E. coli undergoing changes in morphology after incubation with 100 µg ml−1 graphene oxide nanosheets at 37 °C for 2.5 h. Three stages of destruction can be seen. a, Initial morphology of E. coli (control or Stage 1; two individual TEM images (inset and main image) are shown, the scale bar applies to both). b,c, Partial damage of cell membranes, with some bacteria showing a lower density of surface phospholipids (Stage II). Arrows indicate a Type B mechanism, where graphene nanosheets extract phospholipids from the cell membrane. df, Three representative images showing the complete loss of membrane integrity, with some showing ‘empty nests’ and missing cytoplasm (Stage III). d and f are representative images showing a Type A mechanism, where graphene nanosheets cut off large areas of membrane surfaces. In e, both Type A and Type B mechanisms are shown.

  2. Graphene nanosheet insertion and lipid extraction.
    Figure 2: Graphene nanosheet insertion and lipid extraction.

    a,b, Representative simulated trajectories of graphene nanosheet insertion and lipid extraction in the outer membrane (pure POPE) and inner membrane (3:1 mixed POPE–POPG) of E. coli (the snapshot times are shown in the top left corners). Water is shown in violet and the phospholipids in tan lines with hydrophilic charged atoms as coloured spheres (hydrogen, white; oxygen, red; nitrogen, dark blue; carbon, cyan; phosphorus, orange). The graphene sheet is shown as a yellow-bonded sheet with a large sphere marked at one corner as the restrained atom in simulations. Extracted phospholipids are shown as larger spheres.

  3. Interaction energy profiles.
    Figure 3: Interaction energy profiles.

    a,b, Time evolution of the interaction energy between the graphene nanosheet and the membrane (red), the COM of the membrane along the z-direction towards the nanosheet (black) for the representative trajectories shown in Fig. 2 (a, outer membrane; b, inner membrane). c,d, Time evolution of bilayer thickness (red) and area per lipid (black) of membranes in the ‘extracted region’ (c, outer membrane; d, inner membrane). Blue vertical regions indicate the insertion time of the graphene nanosheet in both membranes. Black and green shaded areas indicate the states before and after graphene insertion, respectively.

  4. Lipid extraction by graphene in docking simulations.
    Figure 4: Lipid extraction by graphene in docking simulations.

    af, A representative trajectory of a fully restrained graphene nanosheet docked at the surface of the outer membrane (pure POPE). The simulation time is indicated in each snapshot, with the last snapshot shown in more view angles (e,f, rotated anticlockwise by angle from its previous view to obtain the current view). Colour settings are as in Fig. 2, but with water hidden for clarity.

  5. Robustness of lipid extraction by graphene.
    Figure 5: Robustness of lipid extraction by graphene.

    The average interaction energy between the lipid membrane and the fully restrained graphene nanosheet docked at the membrane surface with different depths of potential well ε'CC. The two different background patterns indicate two distinguished regions, with ε'CC ≤ 1/4εCC and ε'CC > 1/4εCC. It shows that the graphene nanosheet can, in principle, extract phospholipids from the membrane when ε'CC > 1/4εCC (that is, a very robust extraction capability under normal conditions).

  6. Lipid extraction by graphene oxide nanosheets.
    Figure 6: Lipid extraction by graphene oxide nanosheets.

    a,b, Representative configurations of a fully restrained graphene oxide nanosheet docked at both the outer (a) and inner (b) membrane surfaces, with initial conformations shown in side view and final ones shown in top view (both sides). The simulation time is indicated in the top left corner of each snapshot. Colour settings are as in Fig. 2, but with water hidden for a clearer view.

Change history

Corrected online 26 November 2013
In the version of this Article originally published, it was not made clear that the two Escherichia coli cells in the bottom left of Fig. 1a are from a different TEM image to the others. The figure and caption have now been corrected in the PDF and HTML versions of the Article.

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Author information

Affiliations

  1. Institute of Systems Biology, Shanghai University, Shanghai 200444, China

    • Yusong Tu &
    • Zengrong Liu
  2. Division of Interfacial Water and Division of Physical Biology, Shanghai Institute of Applied Physics, Key Laboratory of Interfacial Physics and Technology, Chinese Academy of Sciences, PO Box 800-204, Shanghai 201800, China

    • Yusong Tu,
    • Min Lv,
    • Meng Zhang,
    • Qing Huang,
    • Chunhai Fan &
    • Haiping Fang
  3. Department of Engineering Mechanics and Soft Matter Research Center, Zhejiang University, Hangzhou 310027, China

    • Peng Xiu &
    • Ruhong Zhou
  4. IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598, USA

    • Tien Huynh,
    • Matteo Castelli &
    • Ruhong Zhou
  5. Department of Chemistry, Columbia University, New York 10027, USA

    • Ruhong Zhou

Contributions

R.H.Z., Q.H., H.P.F. and Y.S.T. conceived and designed the experiments and simulations. Y.S.T., P.X., T.H. and M.Z. performed the simulations. M.L. performed the experiments. Y.S.T., P.X., H.P.F., R.H.Z., Q.H., C.H.F. and Z.R.L. analysed the data. Y.S.T., R.H.Z., H.P.F., P.X., M.C., Q.H. and C.H.F. co-wrote the paper. All authors discussed the results and commented on the manuscript.

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The authors declare no competing financial interests.

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