micromachines
ArticleLiposome Deformation Induced by Membrane-Binding Peptides
Kayano Izumi, Chihiro Saito and Ryuji Kawano *Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology,
Tokyo 184-8588, Japan* Correspondence: rjkawano@cc.tuat.ac.jp

Abstract: This paper presents an investigation of liposome deformation and shape distortion using
four membrane-binding peptides: TAT and C105Y as cell-penetrating peptides (CPPs), and melittin
and ovispirin as antimicrobial peptides (AMPs). Liposome deformation was monitored utilizing
fluorescent microscopy, while the binding of peptides to the DOPC membrane was estimated throughcapacitance measurements. The degree of liposome deformation and shape distortion was foundto be higher for the CPPs compared to the AMPs. Additionally, it was observed that C105Y did
not induce liposome rupture, unlike the other three peptides. We propose that these variations inliposome distortion may be attributed to differences in secondary structure, specifically the presenceof an α-helix or random coil. Our studies offer insight into the use of peptides to elicit control ofliposome architecture and may offer a promising approach for regulating the bodies of liposomal
molecular robots.
Keywords: liposome deformation; peptide; membrane capacitance

1. Introduction

Citation: Izumi, K.; Saito, C.;
Kawano, R. Liposome Deformation
Induced by Membrane-Binding
Peptides. Micromachines 2023, 14, 373.
https://doi.org/10.3390/
mi14020373
Academic Editors: Ching-Te Kuo andHsinyu Lee
Received: 26 December 2022
Revised: 25 January 2023
Accepted: 31 January 2023
Published: 2 February 2023

Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Cell-sized liposomes are frequently employed in the study of model cells or cell
membranes. They are also utilized in the field of synthetic biology for encapsulating
materials, particularly in the realm of “Build-a-Cell” research [1,2]. For instance, various
reaction networks utilizing enzymatic and chemical reactions, as well as protein expression,
have been implemented within liposomes [3]. Building upon the technologies of synthetic
biology, the field of molecular robotics has emerged as a subdiscipline, which shares
similarities with “Build-a-Cell” research but addresses challenges from an engineering
perspective [4–6]. A molecular “robot” can be defined as a micro-robot consisting ofmolecules and comprising three essential components: a sensor for perception, a calculator
for intelligence, and actuators for motor function. These functionalities are integrated
within a micron-sized body surrounded by a lipid membrane. In 2017, Sato et al. reported
the prototype of a sophisticated molecular robot, in which they developed an amoeba-type
robot with light-induced DNA clutches for sensors and kinesin-microtubule proteins as
actuators, all integrated within a cell-sized liposome. Light irradiation serves as a trigger
for the release of signaling molecules and engagement of the DNA clutches, leading to achange in the shape of the liposome [7].
The control of liposome shape has been a topic of investigation in molecular robotics,
as deformability is a necessary characteristic for movement within micro and crowded
environments, such as within living organisms or soil. For example, deformable liposomes
containing surfactants have been shown to permeate human skin, enabling the transdermaltransport of drugs [8,9]. Several approaches have been proposed to deform liposomes,
including the use of surfactants [10,11], proteins [3,12,13], and peptides [14–20]. The useof fatty acid surfactants, such as oleate, has been shown to induce the growth, division,and budding of phospholipid or oleate liposomes [10]. Additionally, surfactants havebeen demonstrated to induce shape deformation in fatty acid vesicles, with deformation
dependent on the type of surfactant; for example, the size of vesicles rapidly increases with

Micromachines 2023, 14, 373. https://doi.org/10.3390/mi14020373

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Micromachines 2023, 14, 373

2 of 11the addition of Triton X-100, and sodium dodecyl sulfate induces changes in membrane
curvature [11]. Proteins have also been shown to induce deformation in liposomes throughencapsulated polymerization of cytoskeletal components [12]. For example, Furusato et al.
expressed several proteins involved in the formation of the Z-ring in bacterial cytokinesis
and induced liposome deformation through their presence [3]. Remarkable deformationfrom spherical to other structures was observed under certain conditions, such as in thepresence of FtsZ and ZipA. In the case of using peptides, liposome budding was induced
by a partial sequence derived from matrix-2 (M2), a component of the influenza virus [20].
Additionally, various researchers have reported the use of a venom toxin, melittin, to
induce liposome deformation. As methodologies for peptide design and synthesis havebeen significantly advanced in recent decades, peptides have emerged as a potential
material for the transformation of molecular robots [21].
We here investigated 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) liposome
deformation induced by the following four peptides which are known as antimicrobial
peptides (AMPs) and cell-penetrating peptides (CPPs) which can spontaneously bind tobilayer lipid membranes:(1) Human immunodeficiency virus (HIV)-1 tat (TAT, YGRKKRRQRRR, 11 aminoacids) is derived from 47–57 amino acids of the HIV-1 transcriptional activator [22–25].
(2) C105Y (CSIPPEVKFNKPFVYLI, 17 amino acids) is a synthetic peptide based on
359–374 residues of α1-antitrypsin [24,26].
(3) Melittin (GIGAVLKVLTTGLPALISWIKRKRQQ, 26 amino acids) is derived from
Apis mellifera (a honey bee), and some studies have reported liposome deformation using
this peptide [19,27–32].
(4) Ovispirin (KNLRRIIRKIIHIIKKYG, 18 amino acids) is derived from the N-terminal
18 amino acids of SMAP-29 [33,34].
There have been numerous reports on the secondary structures of the peptides at the
PC membrane including DOPC. The CPPs, such as TAT and C105Y, have been proposed
to exhibit a tendency towards random coil structures [24,25], whereas the AMPs (melittin
and ovispirin) have been suggested to primarily adopt an α-helical structure [28,29,33,34].
In this study, we hypothesized that they may also exhibit random coil and amphipathic
α-helix structures.
To investigate liposome deformation induced by these peptides, we employed fluorescent microscopy and measured membrane capacitance. The latter approach allows forthe determination of changes in membrane properties, such as surface area, permittivity,
and thickness, resulting from peptide binding. Based on our results, we evaluated theeffectiveness of the peptides in inducing liposome deformation.
2. Materials and Methods
2.1. Experimental Materials
In this study, the following chemicals were used: 1,2-dioleoyl-sn-glycero-3-phosphocholine(DOPC; Avanti Polar Lipids, Birmingham, AL, USA), 1,2-dioleoyl-sn-glycero-3phosphoethanolamine-N-(lissamine rhodamine B sulfonyl) (ammonium salt) (Rhodamine
PE; Avanti Polar Lipids, Birmingham, AL, USA), liquid paraffin (FUJIFILM Wako Pure Chemical Corporation, Osaka, Japan), calcein (Sigma-Aldrich Co, LCC., St. Louis, MO, USA),glucose (FUJIFILM Wako Pure Chemical Corporation, Osaka, Japan), sucrose (FUJIFILM
Wako Pure Chemical Corporation, Osaka, Japan), n-decane (FUJIFILM Wako Pure Chemical
Corporation, Osaka, Japan), 3-morpholinopropane-1-sulfonic acid (MOPS, Nacalai Tesque,
Kyoto, Japan), potassium chloride (KCl, Nacalai Tesque, Kyoto, Japan). As peptides, weused C105Y (GenScuript, Piscataway, NJ, USA), melittin (synthesized and purified as powder), ovispirin (KareBay Biochem, Inc., Monmouth Junction, NJ, USA), and TAT (BACHEM,
Bubendorf, Switzerland). Peptides were stored at −20 ◦ C. For use, samples were diluted totheir designated concentration using a buffered electrolyte solution and stored at 4 ◦ C.

Micromachines 2023, 14, 373

3 of 112.2. Preparation of Giant Liposomes Using the Droplet Transfer Method
Liposomes of 98:2 DOPC/Rhodamine PE (mol %) were prepared using droplet transfer. [35] First, 12.1 µL of 32.6 mM lipid mixture dissolved in chloroform was poured into a
glass vial and evaporated under a flow of nitrogen until a lipid film formed at the bottomof the vial. The vial was then put in a desiccator (AZ ONE Corporation, Osaka, Japan) for
more than three hours to completely remove the remaining chloroform. Next, 300 µL of
liquid paraffin was added to the vial and stirred with the lipids using a 40 kHz ultrasoniccleaner MSC-2 (AZ ONE Corporation, Osaka, Japan) at 50 ◦ C for an hour. Then, a 20 µL
liquid mixture of 0.5 M sucrose and 0.5 mM calcein dissolved in MilliQ ultra-pure water(MQ) was added to the vial, and the contents were mixed by tapping 40 times, to form
water-oil (W/O) emulsions. 150 µL of the content was slowly added to 150 µL of 0.5 M
glucose dissolved in MQ in a 500 µL polycarbonate centrifuge tube and centrifuged at
8000× g for 5 min with centrifuge CT15E (Hitachi Koki Co. Ltd., Tokyo, Japan). Giantliposomes were precipitated at the bottom of the tube by the oil-to-water phase transfer ofthe W/O emulsions. The pellet of the liposomes was extracted, resuspended into a newcentrifuge tube with 300 µL of 0.5 M glucose dissolved in MQ, and centrifuged again at
6000× g for 10 min to remove small lipid aggregates. After centrifuging twice, the pellets ofliposomes were loaded into a new centrifuge tube with 100 µL of 0.5 M glucose dissolved in
MQ. All preparations were conducted at room temperature (RT) unless otherwise specified.
Liposomes were observed using an IX71 fluorescence microscope (OLYMPUS Corporation,
Tokyo, Japan). First, we prepared an observing chamber by punching a 6.0 mm hole in asilicon rubber sheet of 5.0 mm thickness and stuck it on the cover glass. 49 µL of liposomes
dissolved in 0.5 M glucose was loaded into the chamber and allowed to settle for at least
15 min to confirm their spherical stability. After the liposomes had settled, 1.0 µL of 50.0 µM
peptide dissolved in 0.5 M glucose was gently loaded into the chamber. Thus, the final
peptide concentration was 1 µM for each peptide–lipid mixture. To minimize the flow ofliposomes, we sunk liposomes near the bottom and observed them in a confined space. The
liposomes were observed through a WIG filter (excitation range: 520–550 nm, Hg-lamp).
Images were recorded using a DFK33UX252 camera (Argo Corporation, Osaka, Japan).
All observations were conducted at RT at least three times. For quantitative analysis, weused Fiji, which is an image-processing package of ImageJ (National Institutes of Health,Bethesda, MD, USA), and Otsu’s threshold clustering algorithm [36].
2.3. Image Analysis of Liposomes
In order to evaluate the deformation of liposomes, we conducted a comprehensive
analysis comprising three distinct components. The first component, referred to as deformation analysis, involved assessing the frequency with which various peptides werecapable of inducing deformation in liposomes. The second component, distortion analysis,
focused on quantifying the degree to which each peptide was able to distort liposomesby measuring the average maximum cross-sectional area (∆Am ) and corresponding time
points of five liposomes selected in descending order of aspect ratio (AR) after peptide
addition. The final component, partial deformation analysis, sought to determine the shapeof the local distortion by comparing the partial deformation of individual liposomes before
and after peptide addition. To this end, we selected two snapshots within the time-lapseof representative deforming liposomes in each condition: one with the median AR before
adding peptides to showcase the mean shape of the spherical liposome and another withthe ∆Am after adding any peptide to demonstrate the distortion.
2.4. Measurement of Membrane Capacitance and Subsequent Analysis
Membrane capacitance (Cm ) was detected using electrophysiological methodologies. [37] First, we fabricated the body of the detection device to have a 6.0 mm thickness
and two separators with 0.2 mm thickness from a polymethyl methacrylate (PMMA) plateusing a three-dimensional modeling machine (MM-100, Modia Systems, Saitama, Japan)(Figure S1). Two chambers with a 2.0 mm diameter and a 4.5 mm depth and a grooveMicromachines 2023, 14, 373

4 of 11

with a 0.45 mm width between the wells were carved on the device. A hole with a 1.0 mm
diameter was carved in each separator. Each chamber in the device had a hole of 0.5 mm
diameter in the bottom, and Ag/AgCl electrodes were set into the hole. A polymeric film
made of parylene C (polychloro-p-xylylene) with a 5.0 µm thickness was patterned with asingle pore of 100 µm diameter using photolithography. The film was sandwiched by two
separators and inserted into the groove of the device to separate the two chambers.
Next, 1.5–2.0 µL of 25.4 µM DOPC dissolved in n-decane and 5.0 µL of a liquid mixtureof 1 µM peptide, 150 mM KCl, and 10 mM MOPS (pH 7) dissolved in MQ were loaded into
chambers in order. To contact the aqueous droplets in two chambers, a bilayer was formedat the parylene pore [38–42]. In addition to applying a +5 mV holding voltage, a +5 mV
square pulse was given at a pulse frequency of 40 kHz. When the capacitance reached theupper limit of the measurement equipment, we stop the measurement. To assess the effectof peptide binding on Cm , we measured the temporal parameters such as resistance (R) andtime constant (τ) with the capacitance. (See also the result) [43]. All data were recordedwith an Axopatch 200B amplifier (Molecular Devices, San Jose, CA, USA) and trials morethan n ≥ 3. The recorded data were analyzed with the Clampex 9.0 software (Molecular
Devices, San Jose, CA, USA).
3. Results
3.1. Microscopic Observation of the Deformation and Rupture of Liposomes by Peptides
Deformation of liposomes was observed through the utilization of fluorescent microscopy for a duration of 30 min following the addition of a peptide at a concentrationof 1 µM. To ensure an adequate resolution, only spherical liposomes with a diameter ofapproximately 6.0 µm were selected; the size distribution is depicted in Figure S2. Uponmonitoring the liposomes, it was observed that some liposomes temporarily disappeared
due to rupture (as illustrated in Figure S3). When adding TAT, melittin, or ovisprin, morethan 80% of liposomes were ruptured within 30 min. In the case of control (without peptide) and C105Y addition, the liposomes were stable, and the rupture was not observedfor 30 min (Figure 1a). Liposome deformation was observed in all cases after adding the
peptide, and the contour of liposomes fluctuated erratically (distortion), or the size ofthe liposomes had changed when compared with the control experiment (Figure 1b–f).
Liposome deformation was analyzed from two parameters: the temporal change of aspectratio (AR) and the change of cross-sectional area (∆A) as defined below:
Ll
Ls

(1)

At
A ave.

(2)

AR =
∆A =

where Ls and Ll are the shortest and longest diameter of a given liposome, At is theapparent cross-sectional area at t seconds after adding the peptides and Aave. is an averagecross-sectional area for a minute before adding peptides, respectively.
Liposomes seem to be slightly deforming without peptides probably due to the convection of the solution. We defined a threshold of large deformation by AR and ∆A basedon the data of the absence of peptides. Deformation of liposomes in this study was definedas over the threshold:
AR > 1.1∆A > 1.1
The AR and the ∆A provide information on the shape distortion and the size changeof liposomes. The order of AR at 30 min was as follows (Figure 1c–f):
TAT > C105Y = ovispirin = melittin
The order of ∆A was:
TAT > C105Y > ovispirin = melittin

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Figure 1. (a) The rupture ratio of liposomes during 30 min after adding five peptides. (b) Images of
Figure 1. (a) The rupture ratio of liposomes during 30 min after adding five peptides. (b) Images ofliposomes without peptide and (c–f) with 1 µM peptide addition. The grey line and red line in theliposomes without peptide and (c–f) with 1 µM peptide addition. The grey line and red line in theright of the images are the tracing outlines of the liposomes before and after adding peptides. The
right of the images are the tracing outlines of the liposomes before and after adding peptides. Thebar
the deforming
deforming ratio
ratio ofofAR
ARandand∆A.
∆A.TheThenumbernumberofoftrials
trialsNbargraphs
graphsshow
show thethe timetime dependence
dependence ofof theN≥ ≥3 andnumberliposomes= 10without
peptide
and
> 20
with
peptide.
3 andthethenumberof ofliposomes
n =n 10without
peptideandn >n20with
peptide.

We
next analyzed
these
deformation
parametersdetail: thedistortion
Liposomes
seem tobe slightly
deforming
withoutinpeptides
probably
due estimatedto the conby
the
AR,
and
the
size
changeestimatedbythe∆A(Figure2a,b).
Regarding
the∆A
AR,
the
vection of the solution. We defined a threshold of large deformation by AR andbased
maximumAR(AR)
ranged
from
1.1
to
1.4,
and
TAT
showedthehighestAR(Figure2c).
mm was definedon the data of the absenceof peptides. Deformation of liposomes in this study
The order of ARm was:as over the threshold:
TAT > C105Y > ovispirin = melittin
AR > 1.1
The observed ARm occurred at different times during the 30 min for each peptide.
∆A > 1.1
Melittin and ovispirin reached the ARm within 10 min, whereas that of TAT and C105Y
The AR and the ΔA provide information on the shape distortion and the size change
were over 10 min (Figure 2d). The time order was similar to the result of AR as follows:of liposomes. The order of AR at 30 min was as follows (Figure 1c–f):
TAT > C105Y > melittin > ovispirin
TAT > C105Y = ovispirin = melittin
As for the ∆A, the maximum ∆A (∆Am ) ranged from 1.1 to 1.4, and TAT also showed
The order of ΔA was:the highest ∆Am (Figure 2e). The order was similar to the result of AR as follows:
TAT > C105Y > ovispirin = melittin
TAT > C105Y > melittin = ovispirin
We next analyzed these deformation parameters in detail: the distortion estimated
These ∆Am were observed before 10 min except for C105Y (Figure 2f). The time orderby the AR, and the size change estimated by the ∆A (Figure 2a,b). Regarding the AR, thewas as follows:
maximum(ARm) rangedfrom>1.1
to 1.4, and TAT showed the highest ARm (Figure 2c).
C105Y AR> melittin≥ ovispirin
TAT
The TheorderofAR
m was:
quantitative estimation of the distortion was performed by analyzing the angleTAT > C105Y= melittin
dependence
radius >ofovispirin
liposomes
as previously proposed in the literature [3]. The normalized radius (Rnor. ) was calculated based on an equation:
Rnor. =R(θ )R ave.

(3)

where Rave. is the average radius, and R (θ) is the radius at each angle (θ), respectively. The
radius of each peptide against the angles is depicted in Figure 2g. The TAT (0.18 ± 0.01)

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6 of 11Micromachines 2023, 14, x FOR PEER REVIEW

6 of 12and C105Y (0.15 ± 0.03) system tended to show a higher amplitude of Rnor . than that of themelittin (0.10 ± 0.02) and ovispirin (0.12 ± 0.01) system.

FigureFigure2.2.Typical
Typicalimages
imagesofofthe
theliposome
liposomedeformation
deformationofof(a)(a)shape
shapedistortion
distortionandand(b)(b)size
sizechangechangebeforeandafteraddingpeptides.
(c)The
maximum
AR
(AR
)
in
the
case
of
addingeachmm) in the case of adding eachpeptide.
before and after adding peptides. (c) The maximum AR (ARpeptide.
(d)(ARm).(e)(e)TheThemaximum
maximum∆A
∆A(∆A
(∆A
inthe
thecasecaseofofadding
addingeacheach(d)TheThetimetimeofofthethemaximum
maximumAR
AR
(AR
m ).
mm))inpeptide.(f)(f)The
Thetimetimeofofmaximum
maximum∆A∆A(∆A(∆A(g)Partial
Partialdistortion
distortionfor
foreacheachcondition.
condition.The
Thedistortions
distortions
peptide.
mm).).(g)eachangle
angle
before(gray)
andafter
addingpeptides(orange)werequantified
bydeviation
the deviation
atateach
before(gray)
andafter
addingpeptides(orange)werequantified
by theof theoftherelative
distancefrom
1.0
indicatingtheradiusoftruecircle.
relative distance from 1.0 indicating the radius of true circle.

3.2. Bindingof PeptideAR
onmtheLipid Membrane
Estimated
the Membrane
Capacitance
The observed
occurredat different
times byduringthe 30 min
for each peptide.
Melittin
ovispirin
reachedthethatARmthewithin10 min,ofwhereasthat of TAT
C105Y
It hasandpreviously
beenreported
capacitancelipid membranes(Cm )andincreases
weretheover
10 minof(Figure
The time order
was similar
thestudy,
result weof AR
as follows:withbinding
added2d).
antimicrobial
peptides[44]. Intothis
estimatedtheTAT
C105Y >TAT,
melittin> ovispirinbindingof >peptides
C105Y,
melittin, and ovispirin to the lipid membrane by meathe ∆A,inthe∆A (∆Ahavem) ranged
from to1.1form
to 1.4,andor
TAT
also during
showedsuringAs
theforincrease
Cmmaximum. These peptides
the ability
pores
defectsthehighest∆A
m(Figure
2e).
The
order
was
similartotheresultofAR
asfollows:
capacitance measurement; thus, we considered the effect of leakage current on Cm . A
generalcapacitanceis givenby the following equation:
TAT> C105Y >(C)melittin= ovispirin
These ∆Am were observed before 10 min except for C105Y (Figure 2f). The time order
C = QV(4)
was as follows:
C105Y > melittin ≥ ovispirin > TAT
where Q is the charge amount and V is the applied voltage.
The quantitative estimation of the distortion was performed by analyzing the angledependence radius of liposomes as previously proposed in the literature [3]. The normalized radius (Rnor.) was calculated based on an equation:

𝑅

. =

𝑅(𝜃)
𝑅 .

(3)

Micromachines 2023, 14, 373

7 of 11

Leakage current should affect the value of current and resistance if the leaking has
occurred. In our experimental system, the temporal current in the circuit (I(t)) is calculated
in the following equation [36]:VRm − tI(t) =
1+e τ(5)Rm + Rs
Rs
where τ =Rm Rs Cm
Rm + Rs(6)

In the equations, Rm is membrane resistance, Rs is the series resistance, total resistance
except for Rm , V is the square pulse voltage, and τ is the time constant. Rs and V are
constant, and Rm and Cm can be affected by the change in current. Equation (6) can beapproximated as follow because the Rm >> Rs in our measurements:τ;

Rm · Rs ·Cm= Rs ·Cm
Rm(7)

Since Rs is constant, the Cm is proportional to τ:τ ∝ Cm(8)

In order to eliminate the influence of leakage currents on our measurements, weestablished time zero as the point at which the capacitance (Cm ) begins to be proportional
to the time constant of current decay (Figure S4). For the purposes of analysis, we restricted
our data to that which adhered to Equations (5)–(8), as the purpose was to estimate thechange in Cm resulting from peptide binding, rather than the effect of leakage currents.
Our calculations indicate that the impact of leakage currents on the continuous increase in
Cm was minimal. In the absence of the peptides, Cm initially increased and then reached aplateau state, as depicted in Figure 3a. This transition from the initial state to the plateau
state is indicative of a shift from lipid monolayer to thinner bilayer formation, as observed
through the droplet contact method employed in this study [45]. In contrast, in the presenceof the peptide, the Cm in the majority of measurements gradually increased from the initialstate and did not reach a plateau state, instead reaching the upper limit of the equipment
within a matter of minutes (Figure 3b–e). The normalized Cm (Cnor. ) was calculated in thefollowing equation:
Cmax(9)
Cnor. =
Ci
where Cmax is the maximum Cm and Ci is the initial Cm at the starting time of the measurements (=time 0). The Cnor. ranged from 1.3 to 1.5 without peptides and from 1.6 to 4.2
with peptides.
We next estimated that the continuous increase showed the peptide binding. Based on
Equation (9), we considered what parameter(s) reflect the increase of the Cm .
The Cm can be defined as:
S
Cm = ε 0 ε r(10)dwhere parameters ε0 , εr , S, and d are the permittivity of a vacuum, relative permittivity, surface area, and thickness of the planar bilayer lipid membrane, respectively. The capacitancedata allows us to infer that peptides are binding to the membrane, as the parameters canvary in response to peptide binding. The variations in the effective lipid bilayer area (S) andthe thickness of the membrane are expected to be minimal in comparison to the changes
in εr as the εr value of peptides (around 54) [46] is significantly greater than that of DOPC
molecules (around 2 to 3) (Figure S5) [47]. Therefore, we consider that the increase in Cm isdue to peptides binding to the lipid membrane and an increase in peptide binding resulting
in the εr increase. In addition, the εr change of the four peptides was similar (around 40 pF,

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8 of 11Micromachines 2023, 14, x FOR PEER REVIEW

8 of 12n ≥ 3, the control was ca. 10 pF, n = 3), indicating a comparable amount of bindings tothelipid membrane.

FigureMembranecapacitancecapacitancemeasurements
measurements
estimating
peptidebinding
the memlipid
Figure 3.
3. Membrane
forforestimating
the thepeptidebindingin theinlipid
brane. (a) without
peptide,(b–e)(b–e)
withwith
peptide.
membrane.
(a) without
peptide,peptide.

4. Discussion
We next estimated that the continuous increase showed the peptide binding. Based
The ability
four
peptides,what
TAT parameter(s)(CPP), C105Yreflect(CPP),themelittin(AMP),
on Equation(9),ofweconsidered
increaseof theandCm. ovispirin(AMP),
to C
induceliposome
was investigated utilizing fluorescence microscopyThem can bedefineddeformationas:and membrane capacitance measurements. The findings of this study revealed that C105Y𝑆(10)
did not exhibit the ability to rupture liposomes,
𝐶 = 𝜀 𝜀unlike the other three peptides, which𝑑caused the disappearance of over 70% of liposomes within 10 min. The amphipathicity of0, beεr, aS,significant
and d are factor
the permittivityof toa vacuum,
relative permittivity,
where parameters
peptideswas found εtoin the ability
rupture liposomes.
[48] C105Y
surfacearea,
andthicknessoftheplanarbilayerlipid
membrane,
respectively.
The capac(17 aa.) has a Glu and two Lys at the 6th, 8th, and 11th positions, and its charge distribution
itancedata
allows
us
to
infer
that
peptidesarebindingtothemembrane,astheparameters
sequence imparts a relatively low degree of amphipathicity [24,26]. In contrast, the othercan varyin response
peptidestronger
binding.amphipathicity
The variationsdue
in theeffective
lipid bilayer
area
three
peptidespossess torelatively
to theiramphipathic
α-helical(S) and thethicknessthe membrane
are expected
to beminimal(TAT).
in comparison to thestructure(melittin
andofovispirin)
and chargepolarization
structurechangesin εrfoundas thethat
εr valueof peptides(around deformation54) [46] is significantly
than wasthat
We next
the capabilityof liposome
used in TATgreaterand C105Y
of DOPC
molecules(around
2 ovispirin.
to 3) (FigureS5) [47].
Therefore,
we consider
the ingreaterthanthat in melittin
andInitially,
it washypothesizedthat thisthat
difference
wasdueintoCvariations
the amountof peptide
binding
to the lipid
However,creasem is due to in
peptidesbinding
to the lipid
membraneand membrane.
an increase in
peptidesubsequent
membrane
capacitancemeasurements
revealedthatthebindingof
peptideswasbinding resulting in the εr increase. In addition, the εr change of the fourwasalmostTherefore,
observedsimilarequivalent(around 40among
pF, n the≥ 3,peptides.
the control
was ca. the
10 pF,
n = 3),differenceindicatinginadeformationcomparable
may
be attributed
to tovariations
the secondary structure of the peptides, which leads toamountof bindings
the lipidin
membrane.
distinct interactions and localization within the lipid membrane. Peptides with random
coil
structures display random-like behavior within the lipid membrane, [24,25], and it has
4. Discussion
been proposed
conventional
toC105Y
lipid membranes
and exhibitakin
The abilitythatof four
peptides,CPPs
TAT bind(CPP),(CPP), melittin(AMP),behavior
and ovispirin
to
that
of
detergentsorform
inverted
micellestructures.
[24,25].
In
contrast,
peptideswith(AMP), to induce liposome deformation was investigated utilizing fluorescence microsan
α-helical
structure haveamphiphilic
properties The
uponbindingoftothis
the study
surfaceof the lipid
copy
and membrane
capacitancemeasurements.
findings
revealedthat
membraneto theformability
a transmembrane
structure or
cover
theothersurfacein peptides,
a carpetC105Y did andnot tend
exhibitto rupture liposomes,
unlike
the
three
like
manner[19,28–34].
This hypothesis
supportedby molecularsimulation
which
causedthe disappearanceof over is70%
of liposomes
within 10dynamics
min. The amphipath(see also supporting description and Figure S6) [49–54]. The secondary structure andicity of peptides was found to be a significant factor in the ability to rupture liposomes.
[48] C105Y (17 aa.) has a Glu and two Lys at the 6th, 8th, and 11th positions, and its charge
distribution sequence imparts a relatively low degree of amphipathicity [24,26]. In con-

Micromachines 2023, 14, 373

9 of 11the membrane-binding mode of these peptides have a significant impact on macroscopic
membrane deformation in liposomes.
5. Conclusions
In conclusion, we investigated the ability of four distinct peptides, CPPs and AMPs, toinduce liposome deformation. The deformation and rupture of liposomes were monitored
using fluorescent microscopy. It was observed that C105Y did not induce liposome rupture
and that the degree of deformation and shape distortion varied between TAT and C105Y(CPPs) and melittin and ovispirin (AMPs). The binding of peptides to the lipid membrane
was estimated using membrane capacitance (Cm ) measurements, which indicated that there
was not a significant difference in the amount of peptide binding among the peptides.
These variations in the effects on liposome deformation may be attributed to variationsin the secondary structures of the peptides when bound to a DOPC membrane. Ourstudies provide insight into the utilization of peptides to control liposome shape andoffer a promising approach for regulating the bodies of liposomal molecular robots. In
future research, we will design peptides capable of controlling liposome deformation,
incorporate these peptides into liposomes, and modulate liposome deformation dependingon the context.
Supplementary Materials: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/mi14020373/s1, Figure S1: the device of capacitance measurement;
Figure S2: size distribution of analyzed liposomes; Figure S3: rupture of liposomes; Figure S4: theprinciple of capacitance detection; Figure S5: correlation between physical parameters and physicalparameters at the membrane; Figure S6: all-atom MD simulation for the migration of 400 ns
Author Contributions: R.K. conceived the original idea; K.I. conducted all experiments and analyzed
the data in this article; C.S. conducted the MD simulation; K.I. and R.K. wrote the paper. All authors
have read and agreed to the published version of the manuscript.
Funding: This research was partially supported by JSPS KAKENHI, grant numbers 21K19786 (R.K.),
and 21H05229 (R.K.). This work was also supported by the Support for Pioneering Research Initiatedby the Next Generation of FLOuRISH Institute, Tokyo University of Agriculture and Technology(TUAT) granted by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan(K.I.), and by the proposal-based Project Fund by the WISE program (K.I.).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Acknowledgments: The authors thank N. Saigo, K. Shimizu, S. Fujita and Z. Peng in our group, andT. Inoue, and H. Matsubayashi of Johns Hopkins University for constructive discussion and advice
on data analysis.
Conflicts of Interest: The authors declare no conflict of interest.

References
1.
2.
3.
4.
5.
6.

Sun, J.; Rijpkema, S.J.; Luan, J.; Zhang, S.; Wilson, D.A. Generating biomembrane-like local curvature in polymersomes via
dynamic polymer insertion. Nat. Commun. 2021, 12, 2235. [CrossRef] [PubMed]
Chen, Z.; Wang, J.; Sun, W.; Archibong, E.; Kahkoska, A.R.; Zhang, X.; Lu, Y.; Ligler, F.S.; Buse, J.B.; Gu, Z. Synthetic beta cells forfusion-mediated dynamic insulin secretion. Nat. Chem. Biol. 2018, 14, 86–93. [CrossRef]
Furusato, T.; Horie, F.; Matsubayashi, H.T.; Amikura, K.; Kuruma, Y.; Ueda, T. De Novo Synthesis of Basal Bacterial Cell Division
Proteins FtsZ, FtsA, and ZipA Inside Giant Vesicles. ACS Synth. Biol. 2018, 7, 953–961. [CrossRef]
Hagiya, M.; Konagaya, A.; Kobayashi, S.; Saito, H.; Murata, S. Molecular Robots with Sensors and Intelligence. Acc. Chem. Res.
2014, 47, 1681–1690. [CrossRef] [PubMed]
Kawano, R. Synthetic Ion Channels and DNA Logic Gates as Components of Molecular Robots. Chemphyschem 2018, 19, 359–366.
[CrossRef] [PubMed]
Shoji, K.; Kawano, R. Recent Advances in Liposome-Based Molecular Robots. Micromachines 2020, 11, 788. [CrossRef]

Micromachines 2023, 14, 373

7.
8.

9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.

24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.

10 of 11Sato, Y.; Hiratsuka, Y.; Kawamata, I.; Murata, S.; Nomura, S.-I.M. Micrometer-sized molecular robot changes its shape in response
to signal molecules. Sci. Robot. 2017, 2, eaal3735. [CrossRef]
Ha, J.H.; Jeong, Y.J.; Kim, A.Y.; Hong, I.K.; Lee, N.H.; Park, S.N. Preparation and Physicochemical Properties of a Cysteine
Derivative-Loaded Deformable Liposomes in Hydrogel for Enhancing Whitening Effects. Eur. J. Lipid Sci. Technol. 2018,
120, 1800125. [CrossRef]
Kim, A.R.; An, H.J.; Jang, E.S.; Lee, J.D.; Park, S.N. Preparation, Physical Characterization, and In Vitro Skin Permeation ofDeformable Liposomes Loaded with Taxifolin and Taxifolin Tetraoctanoate. Eur. J. Lipid Sci. Technol. 2019, 121, 1800501. [CrossRef]Peterlin, P.; Arrigler, V.; Kogej, K.; Svetina, S.; Walde, P. Growth and shape transformations of giant phospholipid vesicles uponinteraction with an aqueous oleic acid suspension. Chem. Phys. Lipids 2009, 159, 67–76. [CrossRef]
Sudbrack, T.P.; Archilha, N.L.; Itri, R.; Riske, K.A. Observing the Solubilization of Lipid Bilayers by Detergents with Optical
Microscopy of GUVs. J. Phys. Chem. B 2011, 115, 269–277. [CrossRef] [PubMed]
Cortese, D.; Schwab, B., III; Frieden, C.; Elson, E.L. Actin polymerization induces a shape change in actin-containing vesicles.
Proc. Natl. Acad. Sci. USA 1989, 86, 5773–5777. [CrossRef] [PubMed]
Tanaka, S.; Takiguchi, K.; Hayashi, M. Repetitive stretching of giant liposomes utilizing the nematic alignment of confined actin.
Commun. Phys. 2018, 1, 18. [CrossRef]
Lee, M.-T.; Hung, W.-C.; Chen, F.-Y.; Huang, H.W. Mechanism and kinetics of pore formation in membranes by water-soluble
amphipathic peptides. Proc. Natl. Acad. Sci. USA 2008, 105, 5087–5092. [CrossRef]
Lee, M.-T.; Sun, T.-L.; Hung, W.-C.; Huang, H.W. Process of inducing pores in membranes by melittin. Proc. Natl. Acad. Sci. USA
2013, 110, 14243–14248. [CrossRef] [PubMed]
Yu, Y.; Vroman, J.A.; Bae, S.C.; Granick, S. Vesicle Budding Induced by a Pore-Forming Peptide. J. AM. CHEM. SOC. 2010,
132, 195–201. [CrossRef] [PubMed]
Takahashi, T.; Nomura, F.; Yokoyama, Y.; Tanaka-Takiguchi, Y.; Homma, M.; Takiguchi, K. Multiple membrane interactions andversatile vesicle deformations elicited by melittin. Toxins 2013, 5, 637–664. [CrossRef]
Yu, Q.; Sun, J.; Huang, S.; Chang, H.; Bai, Q.; Chen, Y.-X.; Liang, D. Inward Budding and Endocytosis of Membranes Regulated byde Novo Designed Peptides. Langmuir 2018, 34, 6183–6193. [CrossRef]
Mally, M.; Majhenc, J.; Svetina, S.; Zeks, B. The response of giant phospholipid vesicles to pore-forming peptide melittin. Biochim.
Biophys. Acta 2007, 1768, 1179–1189. [CrossRef]
Rossman, J.S.; Jing, X.; Leser, G.P.; Lamb, R.A. Influenza virus M2 protein mediates ESCRT-independent membrane scission. Cell
2010, 142, 902–913. [CrossRef]
Shimizu, Y.; Inoue, A.; Tomari, Y.; Suzuki, T.; Yokogawa, T.; Nishikawa, K.; Ueda, T. Cell-free translation reconstituted withpurified components. Nat. Biotechnol. 2001, 19, 751–755. [CrossRef] [PubMed]
Stalmans, S.; Bracke, N.; Wynendaele, E.; Gevaert, B.; Peremans, K.; Burvenich, C.; Polis, I.; Spiegeleer, B.D. Cell-Penetrating
Peptides Selectively Cross the Blood-Brain Barrier In Vivo. PLoS ONE 2015, 10, e0139652. [CrossRef] [PubMed]
Li, S.; Zhang, X.; Guo, C.; Peng, Y.; Liu, X.; Wang, B.; Zhuang, R.; Chang, M.; Wang, R. Hydrocarbon staple constructing highly
efficient alpha-helix cell-penetrating peptides for intracellular cargo delivery. Chem. Commun. 2020, 56, 15655–15658. [CrossRef][PubMed]Kumara, B.T.; Wijesiri, N.K.; Rathnayake, P.V.G.M.; Ranatunga, R.J.K.U. A Re-evaluation of the Free Energy Profiles for CellPenetrating Peptides Across DOPC Membranes. Int. J. Pept. Res. Ther. 2021, 27, 2931–2943. [CrossRef]
Herce, H.D.; Garcia, A.E. Molecular dynamics simulations suggest a mechanism for translocation of the HIV-1 TAT peptide acrosslipid membranes. Proc. Natl. Acad. Sci. USA 2007, 104, 20805–20810. [CrossRef]
Rhee, M.; Davis, P. Mechanism of uptake of C105Y, a novel cell-penetrating peptide. J. Biol. Chem. 2006, 281, 1233–1240. [CrossRef]
Guha, S.; Ghimire, J.; Wu, E.; Wimley, W.C. Mechanistic Landscape of Membrane-Permeabilizing Peptides. Chem. Rev. 2019,
119, 6040–6085. [CrossRef]
Irudayam, S.J.; Pobandt, T.; Berkowitz, M.L. Free energy barrier for melittin reorientation from a membrane-bound state to atransmembrane state. J. Phys. Chem. B 2013, 117, 13457–13463. [CrossRef]
Krauson, A.J.; He, J.; Wimley, W.C. Gain-of-function analogues of the pore-forming peptide melittin selected by orthogonal
high-throughput screening. J. Am. Chem. Soc. 2012, 134, 12732–12741. [CrossRef]
Nguyen, L.T.; Haney, E.F.; Vogel, H.J. The expanding scope of antimicrobial peptide structures and their modes of action. Trends
Biotechnol. 2011, 29, 464–472. [CrossRef]
Miyazaki, Y.; Okazaki, S.; Shinoda, W. Free energy analysis of membrane pore formation process in the presence of multiple
melittin peptides. Biochim. Biophys. Acta Biomembr. 2019, 1861, 1409–1419. [CrossRef] [PubMed]
Geitani, R.; Moubareck, C.A.; Xu, Z.; Karam Sarkis, D.; Touqui, L. Expression and Roles of Antimicrobial Peptides in Innate
Defense of Airway Mucosa: Potential Implication in Cystic Fibrosis. Front. Immunol. 2020, 11, 1198. [CrossRef] [PubMed]
Yamaguchi, S.; Huster, D.; Waring, A.; Lehrer, R.I.; Kearney, W.; Tack, B.F.; Hong, M. Orientation and Dynamics of an Antimicrobial
Peptide in the Lipid Bilayer by Solid-State NMR Spectroscopy. Biophys. J. 2001, 81, 2203–2214. [CrossRef] [PubMed]
Woys, A.M.; Lin, Y.-S.; Reddy, A.S.; Xiong, W.; Pablo, J.J.d.; Skinner, J.L.; Zanni, M.T. 2D IR Line Shapes Probe Ovispirin Peptide
Conformation and Depth in Lipid Bilayers. J. Am. Chem. Soc. 2010, 132, 2832–2838. [CrossRef] [PubMed]
Pautot, S.; Frisken, B.J.; Weitz, D.A. Engineering asymmetric vesicles. Proc. Natl. Acad. Sci. USA 2003, 100, 10718–10721.
[CrossRef]

Micromachines 2023, 14, 373

36.
37.
38.
39.
40.

41.
42.
43.
44.
45.
46.
47.

48.
49.
50.
51.
52.
53.
54.

11 of 11

Schindelin, J.; Arganda-Carreras, I.; Frise, E.; Kaynig, V.; Longair, M.; Pietzsch, T.; Preibisch, S.; Rueden, C.; Saalfeld, S.;
Schmid, B.; et al. Fiji: An open-source platform for biological-image analysis. Nat. Methods 2012, 9, 676–682. [CrossRef]
Kawano, R.; Tsuji, Y.; Sato, K.; Osaki, T.; Kamiya, K.; Hirano, M.; Ide, T.; Miki, N.; Takeuchi, S. Automated Parallel Recordings ofTopologically Identified Single Ion Channels. Sci. Rep. 2013, 3, 1995. [CrossRef]
Sekiya, Y.; Sakashita, S.; Shimizu, K.; Usui, K.; Kawano, R. Channel current analysis estimates the pore-formation and thepenetration of transmembrane peptides. Analyst 2018, 143, 3540–3543. [CrossRef]
Sekiya, Y.; Shimizu, K.; Kitahashi, Y.; Ohyama, A.; Kawamura, I.; Kawano, R. Electrophysiological Analysis of Membrane
Disruption by Bombinin and Its Isomer Using the Lipid Bilayer System. ACS Appl. Bio. Mater. 2019, 2, 1542–1548. [CrossRef]
Shimizu, K.; Mijiddorj, B.; Usami, M.; Mizoguchi, I.; Yoshida, S.; Akayama, S.; Hamada, Y.; Ohyama, A.; Usui, K.; Kawamura, I.; et al. De novo design of a nanopore for single-molecule detection that incorporates a beta-hairpin peptide. Nat.
Nanotechnol. 2022, 17, 67–75. [CrossRef]
Watanabe, H.; Gubbiotti, A.; Chinappi, M.; Takai, N.; Tanaka, K.; Tsumoto, K.; Kawano, R. Analysis of Pore Formation and Protein
Translocation Using Large Biological Nanopores. Anal. Chem. 2017, 89, 11269–11277. [CrossRef] [PubMed]
Hirano, M.; Saito, C.; Yokoo, H.; Goto, C.; Kawano, R.; Misawa, T.; Demizu, Y. Development of Antimicrobial Stapled Peptides
Based on Magainin 2 Sequence. Molecules 2021, 26, 444. [CrossRef] [PubMed]
Okada, Y. Saishin Pacchikuranpu Zikkengizyutsuhou (How to Use Patch-Clamp Method); Yoshioka Shoten: Kyoto, Japan, 2011.
Hagge, S.O.; Wiese, A.; Seydel, U.; Gutsmann, T. Inner Field Compensation as a Tool for the Characterization of Asymmetric
Membranes and Peptide-Membrane Interactions. Biophys. J. 2004, 86, 913–922. [CrossRef] [PubMed]
Funakoshi, K.; Suzuki, H.; Takeuchi, S. Lipid Bilayer Formation by Contacting Monolayers in a Microfluidic Device for Membrane
Protein Analysis. Anal. Chem. 2006, 78, 8169–8174. [CrossRef] [PubMed]
Glattli, A.; Chandrasekhar, I.; van Gunsteren, W.F. A molecular dynamics study of the bee venom melittin in aqueous solution, inmethanol, and inserted in a phospholipid bilayer. Eur. Biophys. J. 2006, 35, 255–267. [CrossRef]
Valincius, G.; Heinrich, F.; Budvytyte, R.; Vanderah, D.J.; McGillivray, D.J.; Sokolov, Y.; Hall, J.E.; Losche, M. Soluble amyloid
beta-oligomers affect dielectric membrane properties by bilayer insertion and domain formation: Implications for cell toxicity.
Biophys. J. 2008, 95, 4845–4861. [CrossRef] [PubMed]
Sun, D.; Forsman, J.; Woodward, C.E. Amphipathic membrane-active peptides recognize and stabilize ruptured membrane pores:
Exploring cause and effect with coarse-grained simulations. Langmuir 2015, 31, 752–761. [CrossRef]
Van Der Spoel, D.; Lindahl, E.; Hess, B.; Groenhof, G.; Mark, A.E.; Berendsen, H.J. GROMACS: Fast, flexible, and free. J. Comput.
Chem. 2005, 26, 1701–1718. [CrossRef]
Huang, J.; Rauscher, S.; Nawrocki, G.; Ran, T.; Feig, M.; de Groot, B.L.; Grubmüller, H.; MacKerell, A.D., Jr. CHARMM36m: An
improved force field for folded and intrinsically disordered proteins. Nat. Methods 2017, 14, 71–73. [CrossRef]
Jo, S.; Kim, T.; Iyer, V.G.; Im, W. CHARMM-GUI: A web-based graphical user interface for CHARMM. J. Comput. Chem. 2008,
29, 1859–1865. [CrossRef]
Parrinello, M.; Rahman, A. Polymorphic transitions in single crystals: A new molecular dynamics method. J. Appl. Phys. 1981,
52, 7182–7190. [CrossRef]
Essmann, U.; Perera, L.; Berkowitz, M.L.; Darden, T.; Lee, H.; Pedersen, L.G. A smooth particle mesh Ewald method. J. Chem.
Phys. 1995, 103, 8577–8593. [CrossRef]
Hess, B.; Bekker, H.; Berendsen, H.J.C.; Fraaije, J.G.E.M. LINCS: A linear constraint solver for molecular simulations. J. Comput.
Chem. 1998, 18, 1463–1472. [CrossRef]

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