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Cite this: DOI: 10.1039/c8an00243f
Received 7th February 2018,
Accepted 28th April 2018
DOI: 10.1039/c8an00243f
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Channel current analysis estimates the poreformation and the penetration of transmembrane
peptides†Yusuke Sekiya,a Shungo Sakashita,b Keisuke Shimizu,a Kenji Usui
Ryuji Kawano *a

We measured the current signal of the transmembrane model peptides using the barrel-stave, toroidal pore, and penetration models
in order to establish a precise assignment of the channel signals. In
addition, we analyzed the spike signals to estimate the membrane
penetration of model cell-penetration peptides of diﬀerent lengths.

Short transmembrane peptides (∼50 amino acids) including
pore-forming or cell-penetration peptides (CPPs) have important biological functions such as antimicrobial activities ormass transport through cell membranes.1,2 Elucidating thestructure–function associations of transmembrane peptides isof considerable scientific interest for the understanding of
mechanisms and for medical applications; however, the development of methodologies for structural analysis in lipid membranes remains a challenge. In the case of large membraneproteins such as ion channels or receptors (∼100 kDa), protein
structures have been experimentally elucidated with high accuracy using X-ray crystallography, electron microscopy, andatomic force microscopy.3–5 However, in the case of short peptides, the determination of the structure is impossible using
the above methods because of their small molecular size.
While spectroscopic methods such as solid-state NMR,6,7 circular dichroism (CD) spectroscopy, including oriented CD withliposomes,8,9 and surface plasmon resonance (SPR)10,11 areconventionally used for this analysis, high accuracy of thestructure is diﬃcult to obtain using spectroscopic methods.
We proposed that a channel current method would be aneﬀective tool for the structural analysis of pore-forming peptides such as antimicrobial peptides (AMPs).12–14 AMPs killbacteria by forming pores or defects in their cell membranes,
resulting in cell lysis. Pore formation can be monitored viaaDepartment of Biotechnology and Life Science, Tokyo University of Agriculture andTechnology, 2-24-16 Naka-cho, Koganei, Tokyo 184-8588, Japan.
E-mail: rjkawano@cc.tuat.ac.jpb
FIRST (Faculty of Frontiers of Innovative Research in Science and Technology),
Konan University, 7-1-20 Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan† Electronic supplementary information (ESI) available: All experimental procedures and figures. See DOI: 10.1039/c8an00243f

This journal is © The Royal Society of Chemistry 2018bandchannel-current measurement using a planar bilayer lipid
membrane ( pBLM) as the artificial cell membrane; current
signals associated with various types of transmembrane
peptide structures are shown in Fig. 1a–c. Traditionally,
channel current measurements using pBLMs require considerable operator proficiency for membrane formation, and thestability of these membranes is not enough to acquire large
datasets for stochastic analysis. We have developed a stable
and reproducible method for pBLM formation using microfabricated and microfluidic technologies;15,16 the microdevice ispresented in Fig. 1d. Our proposed droplet contact method
uses two microdroplets surrounding a lipid monolayer, and it
brings these droplets into contact with each other forming alipid bilayer at the interface of the droplets. Due to the highstability of the pBLM in this method, we have successfullymeasured several ion channels,16 pore-forming proteins,12 andsynthetic channels,17 obtaining large datasets, and we havealso applied parallel nanopore measurements for single molecule detection.18–20
Several diﬀerent current–signal shapes appeared in thechannel recordings, and we classified the four types of current
signals according to the signal classification of synthetic channels, as previously proposed.21 Furthermore, we haveattempted to assign these signals to the specific models of previously reported peptide structures,1,22 as described below.14(1) Step-like signal: In this type of current signal, the current
jumps up orthogonally and maintains a plateau state. Thissignal can apply to the “barrel-stave model”, wherein transmembrane peptides are tightly assembled with each other andform a rigid circular pore (Fig. 1a).
(2) Multi-level signal: In this type of current signal, thecurrent shows fluctuation after jumping up and returns to theinitial state. This current may indicate a “toroidal” model,
wherein transmembrane peptides form a pore with lipids. In
this model, the size of the pore can change dynamically withor without the participation of the lipid between the monomers (Fig. 1b).
(3) Erratic signal: In this type of current signal, the current
presents random increases with fluctuation. We assigned thisAnalystView Article Online

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AnalystFig. 1 Classiﬁcation of the channel current signals of pore-forming peptides and possible models of the mechanisms from among those previously
proposed. The typical current signals of step-like (a), multi-level and erratic (b), and spike (c) with an illustration of our proposed models. (d)Photograph of the pBLM array. In this system, eight detachable devices prepare the eight independent lipid bilayers simultaneously. A device has twochambers with electrodes that are separated by a separator.

signal to the “carpet” model. The carpet model has been
described as peptides that bind parallel to the lipid bilayer
surface and, after reaching suﬃcient coverage, unwrap lipids
as a peptide–lipid cluster from the membrane, similar to a
detergent. The random current behavior of the erratic signal
might be caused by the random size of the cluster (Fig. 1b).
(4) Spike signal: In this type of current signal, the current
suddenly increases and then returns to the baseline over a
period of less than 20 ms. This signal indicates an instantaneous membrane defect. We applied this signal to peptide
permeation through the membrane (Fig. 1c).
Detailed signal classification is described in the ESI.†
To construct a more probable assignment, in this study, wemeasured three characteristic peptides (Table S1†): magainin-1
was used as the toroidal pore model peptide,23,24 alamethicin
was used as the barrel-stave dominant peptide,25,26 and the LK
peptide was used as the CPP.27,28 The current signals of these
peptides were classified using the above-mentioned
classification.
Magainin-1 is a popular AMP, discovered in the skin of theAfrican clawed frog Xenopus laevis.24 In the current recordings,
all 4 current signals were observed, as shown in Fig. 2a. These
peptides should interact not only with each other but also withlipid molecules. They sometimes self-assemble into a barrelstave pore, showing step-like signals. In other cases, they form
the toroidal pore with lipid molecules or a carpet model structure. They also directly penetrate through the lipid membrane.
The signal classification in Fig. 2a suggests that all the
4 models randomly appeared in the magainin1 measurements.
Fig. 2b represents the results of alamethicin measurements.
Alamethicin is a 20-residue sequence high in 2-aminoisobuty-

AnalystFig. 2 Signal classiﬁcation of three kinds of peptides. The number ofcircular graphs indicates the percentages of each signal (n = 87–146).

ric acid (Aib) that forms a 310-helical (3 residues per turn)structure.29 This peptide is well known for its formation of thebarrel-stave pore. In fact, the obtained currents showed thestep-like signal in over 90% of all the observed signals. The
barrel-stave structure forms a rigid transmembrane pore
because of the strong peptide–peptide interactions. The

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Analystcurrent fluctuating up and down reflects the additionalmonomer insertion into the assembling pore, or the desorption of monomers from the pore.30
LK peptides consist of a leucine (L)–lysine (K) sequence,and they are well known as CPPs.28,31 The single LK peptide
unit is [LKKLLKL], named L4K3. In this study, we used several
lengths of LK peptides: L8K6, L12K9, and L16K12 named[LKKLLKL]2, [LKKLLKL]3, and [LKKLLKL]4, respectively. The
LK peptides have an α-helical structure and have periodic distribution of hydrophobic and hydrophilic regions in the
peptide, which serve to stabilize the peptide’s secondary structure.32 Although arginine-rich peptides (e.g., R9) are also wellknown as CPPs,33 their secondary structure is almost arandom coil. Therefore, we selected α-helical LK peptides as
the membrane penetration peptides to maintain a consistentsecondary structure across all the selected experimental peptides. Fig. 2c depicts the typical current traces and the signal
classification of the L8K6 peptide. The spike signal was dominant in this measurement, suggesting that the peptides may
form lipid membrane defects momentarily as they translocate
through the membrane, as proposed by the Shai–Matsuzaki–
Huang model.34 Although most conventional methods require
fluorescent labeling to study membrane penetration, thecurrent recording method does not require fluorescent labeling; therefore, this direct observation of the penetration
phenomenon reveals the molecular mechanism of CPP
directly.
Next, we attempted to analyze the spike signals of the L8K6
peptide using 3 parameters: the current amplitude, which
gives information on the size of the defect in the membrane;
the duration time, which reflects the duration of the defect formation; and the time between spike signals, which shows theevent frequency of the penetration (Fig. 3a). Fig. 3b depicts theCommunication

scatter plots for the current amplitudes and duration time of
the L8K6 peptide. The amplitude and duration range from 10
to 100 pA and from 0.1 to 10 ms, respectively. The dependenceof these 3 parameters on peptide length was also studied. The
duration and peak amplitude did not reveal significant diﬀerences between diﬀerent peptide lengths, although the valuesof L12K9 were slightly lower than those of all other peptides(Fig. 3c and d). However, the time between peaks was thehighest for L12K9, as shown in Fig. 3e. The histograms andvalues of all data are presented in Fig. S2† and Table 1. The
peak in Fig. 3e indicates that the kinetics of membrane penetration decreases with increasing molecular size up to L12K9
whereas penetration dynamics are similar regardless of size.
However, regarding the kinetics of L16K12, the event frequency
increased even in the largest molecular structure. This peptide
forms a strong α-helical structure in the aqueous phase, as
observed from circular dichroism measurements (Fig. S3b†),which may induce peptide binding on the membrane surface.
These peptides show relatively higher event frequency, whichmight be owing to their concentration at the membranesurface. In addition, the length of L16K12 (ca. 4 nm: thelength of the [LKKLLKL] unit is ca. 1 nm) is almost comparTable 1 Properties of LK peptides. Helicity was calculated using [θ]222 nm. Rate constant [s−1] is the reciprocal of time between spikes [s].
Duration time, peak current, and rate constant are median values (n >100)

Helicity, buﬀer [%]Helicity, liposome [%]Duration time [ms]Peak current [pA]
Rate constant [s−1]

L4K3

L8K6

L12K9

L16K12

0
0
0.69
32.7
21.7

0
15.5
0.75
32.7
4.08

1.3
55.8
0.63
19.1
3.71

58.7
58.5
0.75
41.0
7.68

Fig. 3 (a) Typical current–time spike signal traces of the L8K6 peptide. We analysed the spike current amplitude (red), duration time (blue), and time
between spikes (black). (b) Scatter plots of peak current amplitudes and duration time of L8K6 peptides. The repeat length dependency of the LK
peptides for (c) the duration time, (d) the peak current, and (e) time between spikes, as mean values. Histograms of all data are shown in Fig. S2.†This journal is © The Royal Society of Chemistry 2018

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able to the thickness of the lipid bilayer in this system. Thismight cause the higher event frequency. The event rate constant of each peptide is summarized in Table 1. These values
are much higher than the value of tat peptide uptake in living
cells (∼10−3 s−1),2 implying higher membrane penetration
kinetics in this system.
In summary, to reveal the molecular mechanism of membrane penetration by short peptides in the lipid bilayer, weclassified the current signals of three α-helical peptides using
the microfabricated pBLM device, and assigned the signals tothe possible structural models in a lipid membrane. The step,
multi-level/erratic, and spike signals are assigned as barrelstave, toroidal pore, and penetration models, respectively,
using three typical model peptides: magainin-1, alamethicin,
and LK peptides. In addition, we analyzed the spike signals
assigned to the membrane penetration, and concluded thatthe dynamics and kinetics of the membrane penetration may
be estimated using the spike amplitude, duration time, andrate constant. Our proposed method using channel current
analysis could be a strong candidate for investigating membrane binding peptides at the molecular level.

Conﬂicts of interest
There are no conflicts to declare.

Acknowledgements
This work was partially supported by KAKENHI: Grant No.
16H06043 (RK), 17K19138 (RK), and 15H00828 (KU) from
MEXT, Japan.

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