Bin Ni1,2, Remy Colin1,2, Victor Sourjik1,2. 1. Department of Systems and Synthetic Microbiology, Max Planck Institute for Terrestrial Microbiology, Marburg D-35043, Germany. 2. LOEWE Center for Synthetic Microbiology (SYNMIKRO), Philipps University Marburg, Marburg D-35043, Germany.
Abstract
Minicells are nanosized membrane vesicles produced by bacteria. Minicells are chromosome-free but contain cellular biosynthetic and metabolic machinery, and they are robust due to the protection provided by the bacterial cell envelope, which makes them potentially highly attractive in biomedical applications. However, the applicability of minicells and other nanoparticle-based delivery systems is limited by their inefficient accumulation at the target. Here we engineered the minicell-producing Escherichia coli strain to overexpress flagellar genes, which enables the generation of motile minicells. We subsequently performed an experimental and theoretical analysis of the minicell motility and their responses to gradients of chemoeffectors. Despite important differences between the motility of minicells and normal bacterial cells, minicells were able to bias their movement in chemical gradients and to accumulate toward the sources of chemoattractants. Such motile and chemotactic minicells may thus be applicable for an active effector delivery and specific targeting of tissues and cells according to their metabolic profiles.
Minicells are nanosized membrane vesicles produced by bacteria. Minicells are chromosome-free but contain cellular biosynthetic and metabolic machinery, and they are robust due to the protection provided by the bacterial cell envelope, which makes them potentially highly attractive in biomedical applications. However, the applicability of minicells and other nanoparticle-based delivery systems is limited by their inefficient accumulation at the target. Here we engineered the minicell-producing Escherichia coli strain to overexpress flagellar genes, which enables the generation of motile minicells. We subsequently performed an experimental and theoretical analysis of the minicell motility and their responses to gradients of chemoeffectors. Despite important differences between the motility of minicells and normal bacterial cells, minicells were able to bias their movement in chemical gradients and to accumulate toward the sources of chemoattractants. Such motile and chemotactic minicells may thus be applicable for an active effector delivery and specific targeting of tissues and cells according to their metabolic profiles.
Entities:
Keywords:
chemotaxis; drug delivery; minicell; motility; nanoparticle
Nanoparticles are highly
promising as containers for targeted drug
delivery in such biomedical applications as tumor therapy, and a large
spectrum of different nanoparticle designs has been developed over
the recent years.[1−3] Nevertheless, the efficiency of drug delivery by
nanoparticles remained relatively low,[3] with a particular challenge being to enrich nanoparticles within
the targeted tissues. One type of nanosized delivery vehicles is bacterial
minicells, ∼0.5 μm spheres surrounded by a cell envelope,
which are spontaneously generated through an aberrant division of
bacteria close to cell poles. The production of minicells is particularly
frequent in bacterial min mutants that have lost
control of the cell-division site placement.[4,5] Minicells
carry no chromosomes and are therefore nonliving, but they can contain
plasmid DNA and other cellular components, including metabolic enzymes
and cellular machineries that are required for energy generation and
for transcription and translation.[5,6] Hence, minicells
are metabolically and biosynthetically active, meaning that—similar
to the intact bacteria—they can be utilized as specific biosensors[7] and engineered to express a wide range of toxins,
cytokines, tumor antigens, and apoptosis-inducing factors under the
control of specific external stimuli.[8] Because
of the protection provided by the bacterial cell wall and membranes,
minicells are highly robust and do not spontaneously release their
content. Their small size enables minicells to penetrate fenestrated
blood vessels and to accumulate at tumor sites, where they can be
subsequently endocytosed and release their content within the target
cells.[9] Minicells were engineered to target
cancer cells via bispecific antibodies and equipped with various payloads
including chemotherapeutic drugs or inhibitory RNAs[9−14] as well as with a secretion system for antigen injection into the
host cells.[15]Intact bacteria can
also be utilized as drug delivery vehicles,
with the bacterial ability to swim in liquid media providing a particular
advantage for efficient delivery. The bacterial swimming motion is
typically mediated by the rotation of several flagellar filaments
that bundle together to propel the cell,[16] and it can be biased in chemical gradients by the chemotaxis signaling
pathway. This pathway perceives temporal changes in chemical stimulation
as cells swim in the gradient, and it signals to flagellar motors
to modulate the frequency of cell reorientation, thereby increasing
the duration of cell runs in a favorable direction.[17,18] This mechanism of gradient sensing by temporal comparisons of ligand
concentration along the swimming path is necessary because of the
small size of bacteria, and it is physically limited by a gradual
reorientation of the cell body due to Brownian diffusion or—at
high cell densities—to the emergent collective motion.[19−21] Because of this importance of rotational diffusion, the processivity
of swimming and thus efficiency of chemotaxis can increase with bacterial
cell length.[22,23]Bacterial chemosensory
systems were reported to perceive chemical
signals released by the host epithelium[24−26] and in tumor microenvironments,[27,28] indicating that chemotaxis could be applicable for specific tumor
targeting. Furthermore, flagellar motility can promote an attachment
to epithelial cells[29] and tissue penetration.[30,31] Motile bacteria can also be specifically loaded with cargo nanoparticles
carrying customized therapeutics,[32] and
such bacteriabots are chemotactic as long as the cargo does not strongly
reduce their swimming speed.[22] However,
despite these potential advantages for autonomous active delivery,
the in vivo application of intact bacteria remains
severely limited by biosafety concerns.Here we report a system
that combines advantages provided by small
and chromosome-less minicells with the chemotactic capability of motile
bacteria. We engineered an Escherichia coli strain
that produces minicells with an inducible expression of the flagellar
system and investigated their motility and chemotaxis. We demonstrate
that, at higher levels of flagellar gene expression, these minicells
are well-motile, despite their small size and hence small number of
flagella and faster rotational diffusion. Moreover, although minicells
were previously shown to contain functional chemosensory complexes,[33,34] it was unclear whether their swimming could be fast and processive
enough to enable a proper functioning of the bacterial chemotaxis
strategy. We show that, despite these potential limitations, the chemotactic
efficiency of minicells is comparable to that of regular bacteria,
and we develop an analytical model of the minicell motility that can
largely account for our experimental observations. This proof-of-concept
implementation of motility and chemotaxis in minicells makes it possible
to further increase the efficiency of minicell-based drug delivery
as well as its specific targeting relying on chemical gradients emanating
from particular microenvironments such as tumors.
Results and Discussion
Engineering E. coli for an Inducible Production
of Flagellated Minicells
To generate minicells, we used a
derivative of the E. coli strain MG1655 that carries
a deletion of the minCDE operon encoding the division-site
positioning system. This deletion results in frequent cell divisions
at cell poles, pinching off multiple minicells.[5] We further introduced an A115V amino acid replacement in
the actin-like protein mreB, which decreases the E. coli width and therefore leads to the production of minicells
with even smaller diameter.[34] Whereas cells
of the wild-type strain MG1655 are ∼2.3 μm long and ∼1
μm wide when grown in tryptone broth (TB) (Figure S1A,B), the minCDE mreBA115V strain is elongated and produces spherical minicells of 440 ±
49 nm diameter (Figure A–-E). We observed that our minCDE mreBA115V strain also acquired a spontaneous (apparently adaptative)
deletion that inactivated the operon encoding flhDC, the upstream master regulator of the flagellar regulatory network
(Figure S2A), thus effectively shutting
down the expression of all flagellar genes. Consequently, both minicell-producing
mother cells (Figure A) and minicells (Figure B) were not flagellated. In order to tune the levels of flagellar
and chemotaxis proteins, we engineered this strain to express the flhDC operon from a plasmid under an arabinose-inducible
promoter. The induction of flhDC expression in minicell-producing
mother cells indeed led to the increased activity of the flagellin
(fliC) promoter (Figure S2B,C) that is representative for the expression of flagellar and chemotaxis
genes (Figure S2A).[35,36] Consistently, the activation of flagellar gene expression led to
the appearance of flagellar filaments in both mother cells (Figure C and Figure S3A,B) and in minicells (Figure D,F,G and Figure S3C,D). On average, flagellar filaments in minicells
were ∼7.5 μm in length (Figure G and Figure S4A), similar to the length of flagellar filaments in the parental MG1655
cells (Figure S1C). The filament length
remained constant over the whole range of the flhDC expression levels, above the initial activation threshold (Figure G and Figure S4A), whereas the number of flagellar
motors increased with induction up to a maximum of approximately two
motors per minicell (Figure F and Figure S4B).
Figure 1
Flagellation of minicells
dependent on the induction of flhDC expression. (A–D)
Negative staining electron
microscopy images of E. coli minicell-producing strain
(A, C) and of purified minicells (B, D) for cultures of the minicell-producing
strain without the flhDC expression construct (A,
B) or upon induction of the flhDC expression with
0.01% arabinose (C, D). Scale bars are 1 μm. (E) Distribution
of the minicell size measured in the electron microscopy images as
in (D). (F–G) Dependence of flagellar number (F) and flagellar
length (G) in minicells, measured in the electron microscopy images,
on PfliC promoter activity in the minicell-producing
culture. Colors indicate different levels of flhDC induction (Figure S2B,C). Solid lines
are hyperbolic fits to the data for visualization. Error bars indicate
the standard deviation for 10–25 flagella measured at each
condition.
Flagellation of minicells
dependent on the induction of flhDC expression. (A–D)
Negative staining electron
microscopy images of E. coli minicell-producing strain
(A, C) and of purified minicells (B, D) for cultures of the minicell-producing
strain without the flhDC expression construct (A,
B) or upon induction of the flhDC expression with
0.01% arabinose (C, D). Scale bars are 1 μm. (E) Distribution
of the minicell size measured in the electron microscopy images as
in (D). (F–G) Dependence of flagellar number (F) and flagellar
length (G) in minicells, measured in the electron microscopy images,
on PfliC promoter activity in the minicell-producing
culture. Colors indicate different levels of flhDC induction (Figure S2B,C). Solid lines
are hyperbolic fits to the data for visualization. Error bars indicate
the standard deviation for 10–25 flagella measured at each
condition.
Motility and Chemotaxis
of Flagellated Minicells
To
investigate whether flagellated minicells generate enough energy to
power the rotation of flagellar motors, and whether a rotation of
one to two flagellar filaments produces a sufficient force to processively
propel the minicell, we next compared the motion of nonflagellated
and flagellated minicells. Consistent with them lacking an active
propulsion system, trajectories of nonflagellated minicells were clearly
Brownian (Figure A).
In contrast, trajectories of flagellated minicells showed significantly
persistent swimming (Figure B and Figure S5), comparably to
the trajectories of the parental MG1655 cells (Figure S5D). Cell tracking confirmed that, as expected for
diffusive behavior, the mean squared displacement (MSD) increases
linearly as a function of time for nonflagellated minicells (Figure D) and that the distribution
of their displacements is Gaussian (Figure S5A). For flagellated minicells and MG1655 cells, the MSD grows quadratically
with time (Figure D), which is characteristic for a ballistic motion. Distributions
of displacements were also similar for flagellated minicells and MG1655
cells (Figure S5A), with minor differences
being likely explained by a slightly higher fraction of minicells
that were nonmotile, ∼10–30% (independent of flhDC induction) compared to 5–10% for MG1655, as
determined by microscopy analysis (see Materials
and Methods). This subpopulation of nonmotile minicells might
arise from cell or flagella damage during the culture preparation
or from the residual heterogeneity of the flhDC induction
(Figure S2C). The average velocity of swimming
minicells saturated below 15 μm/s (Figure C), which is significantly lower than the
velocity of MG1655 cells (24 μm/s). In contrast, the duration
of runs was longer for the swimming minicells (Figure E). Finally, consistent with their small
size, swimming minicells were reoriented more rapidly due to the rotational
diffusion, being thus less able to maintain their swimming direction
than normal E. coli cells (Figure F).
Figure 2
Motility of flagellated minicells. (A, B) Trajectories
of minicells
without flagellar filaments (A) strain without the flhDC expression construct) or with flagellar filaments upon induction
of flhDC expression with 0.01% arabinose (B). (C)
Dependence of the average velocity of minicells on flagellar gene
expression. Error bars indicate the standard deviation for three independent
measurements. (D–F) Characterization of the cell motion for
minicells carrying either an empty vector or the flhDC expression plasmid induced with indicated concentrations of arabinose.
Data for MG1655 cells, measured previously,[47] are shown for comparison. (D) The mean squared displacement MSD(t) as a function of the lag time t, shown
on a logarithmic scale. Black bars indicate the power laws MSD(t) ∝ t (corresponding to diffusive
behavior) and MSD(t) ∝ t2 (corresponding to ballistic motion) as labeled. (E) Mean
durations of the minicell runs. Statistical significance was evaluated
using an unpaired Student t-test. (F) The time autocorrelation
function of the direction of swimming ⟨u(t)u(0)⟩ as a function of the lag time t. Multitime scale decay, expected given the various processes
contributing to minicell reorientation, was fitted as a stretched
exponential (solid line) exp(−(λt)β), yielding the typical decay time λ. The stretching
exponent is β = 0.7 for the minicells, and β = 1 for normal
MG1655 cells. (D–F) Error bars are the standard error of the
mean on four (motile cells) or two (empty plasmid) independent data
sets.
Motility of flagellated minicells. (A, B) Trajectories
of minicells
without flagellar filaments (A) strain without the flhDC expression construct) or with flagellar filaments upon induction
of flhDC expression with 0.01% arabinose (B). (C)
Dependence of the average velocity of minicells on flagellar gene
expression. Error bars indicate the standard deviation for three independent
measurements. (D–F) Characterization of the cell motion for
minicells carrying either an empty vector or the flhDC expression plasmid induced with indicated concentrations of arabinose.
Data for MG1655 cells, measured previously,[47] are shown for comparison. (D) The mean squared displacement MSD(t) as a function of the lag time t, shown
on a logarithmic scale. Black bars indicate the power laws MSD(t) ∝ t (corresponding to diffusive
behavior) and MSD(t) ∝ t2 (corresponding to ballistic motion) as labeled. (E) Mean
durations of the minicell runs. Statistical significance was evaluated
using an unpaired Student t-test. (F) The time autocorrelation
function of the direction of swimming ⟨u(t)u(0)⟩ as a function of the lag time t. Multitime scale decay, expected given the various processes
contributing to minicell reorientation, was fitted as a stretched
exponential (solid line) exp(−(λt)β), yielding the typical decay time λ. The stretching
exponent is β = 0.7 for the minicells, and β = 1 for normal
MG1655 cells. (D–F) Error bars are the standard error of the
mean on four (motile cells) or two (empty plasmid) independent data
sets.To further test whether, despite
these differences in their swimming
behavior, motile minicells are capable of performing chemotaxis, we
probed the motility of minicells in gradients of α-methyl-d,l-aspartate (MeAsp), a nonmetabolizable analogue
of aspartate and potent chemoattractant for E. coli. We first used a previously described microfluidic device (Figure A inset) that allows
measurements of the chemotactic drift of a bacterial population in
a steady linear chemical gradient.[35,37] A significant
population drift up the MeAsp gradient could be observed, with the
drift velocity of the minicell population growing with flagellar gene
expression (Figure A). This drift velocity apparently increased linearly as a function
of the average number of flagellar motors of the minicells (Figure B). Thus, although
a single flagellum might already be sufficient to propel a minicell
at nearly maximum speed, the efficiency of the chemotaxis is apparently
higher for minicells that are propelled by two flagella. This higher
efficiency might stem from physical effects of the number of flagella
on the tumbling rate and processivity of swimming and/or from an increased
expression of chemotaxis proteins at higher levels of flhDC induction (Figure S2A and Supporting Information). Notably, even at the
highest induction of flagellar genes the chemotactic drift of the
minicells ( μm/s)
remained lower than the one
of the parent MG1655 cells ( μm/s).
Figure 3
Chemotaxis
of minicells. (A, B) Drift velocity of minicells in
a linear gradient of MeAsp (0–100 μM) formed in the microfluidic
device shown in inset, as a function of the flagellar
gene expression (A) and the flagellar number (B). Error bars for the
drift velocity values indicate standard deviation for three independent
measurements. Values for the flagellar numbers are taken from Figure F. (C, D) Schematic
representation of the microfluidic chip used for the minicell chemotaxis-mediated
accumulation analysis (C) and microscopic image (top view) of the
observation channel used to determine chemotactic accumulation (D).
The observation channel connects a well containing the chemoattractant
MeAsp (2 mM) (right side; source) with another well containing the
minicell suspension (left side; sink). See Figure S6 for the exact design and dimensions of the microfluidic
chip. (E–H) Accumulation of sfGFP-expressing minicells in the
observation channel in the presence or absence of MeAsp. Numbers of
minicells under indicated conditions (E) and representative images
showing the accumulation of motile minicells in the presence (F) or
absence (G) of MeAsp in the source chamber, as well as nonflagellated
minicells (H) in a chamber with a MeAsp gradient as control. Error
bars in (E) indicate the standard deviation for three independent
measurements.
Chemotaxis
of minicells. (A, B) Drift velocity of minicells in
a linear gradient of MeAsp (0–100 μM) formed in the microfluidic
device shown in inset, as a function of the flagellar
gene expression (A) and the flagellar number (B). Error bars for the
drift velocity values indicate standard deviation for three independent
measurements. Values for the flagellar numbers are taken from Figure F. (C, D) Schematic
representation of the microfluidic chip used for the minicell chemotaxis-mediated
accumulation analysis (C) and microscopic image (top view) of the
observation channel used to determine chemotactic accumulation (D).
The observation channel connects a well containing the chemoattractant
MeAsp (2 mM) (right side; source) with another well containing the
minicell suspension (left side; sink). See Figure S6 for the exact design and dimensions of the microfluidic
chip. (E–H) Accumulation of sfGFP-expressing minicells in the
observation channel in the presence or absence of MeAsp. Numbers of
minicells under indicated conditions (E) and representative images
showing the accumulation of motile minicells in the presence (F) or
absence (G) of MeAsp in the source chamber, as well as nonflagellated
minicells (H) in a chamber with a MeAsp gradient as control. Error
bars in (E) indicate the standard deviation for three independent
measurements.We further confirmed that chemotactic
minicells can efficiently
accumulate toward the sources of chemoattractants, by using another
microfluidic device where MeAsp is continuously released at the end
of the channel[38−40] (Figure C,D and Figure S6). This device
mimics natural situations where chemoeffectors are released by a source,
such as tumor tissue. Consistent with their ability to perform chemotaxis,
minicells showed an increased migration into the observation channel,
thus accumulating toward the source of attractant (Figure E,F). No accumulation was observed
in the absence of MeAsp in the microfluidic chamber (Figure E,G) or for nonmotile minicells
(Figure E,H).
Modeling
of Motility and Chemotaxis of Minicells
In
order to better understand physical limitations on the swimming and
chemotaxis of minicells, we used a common model for the chemotactic
drift of E. coli (Supporting Information).[20,41−43] The chemotactic
drift is described in this model as a function of biochemical properties
of the signaling pathway as well as of the physical parameters that
characterize cell swimming. We assumed that the functioning of the
chemotaxis pathway in minicells is similar to that of the normal cells.[33] Two important physical parameters, which are
affected by the cell dimensions, are the rotational diffusion coefficient
for swimming cells Dr and the tumble persistence
time τT (Figure ). According to our data (Figure F), minicells are less able to keep swimming
in a given direction, with the rotational diffusion coefficient of
the minicells being s–1 and therefore much
larger compared with for normal cells.[19] This increase is
well-accounted for by a simple model of rotational
diffusion that considers the rotation of the cell body and the flagellum
(Supporting Information).[44,45] The tumble persistence time measures the time it takes for a cell
to randomize its direction of motion via tumbling. It is expected
to be , where τ0 is the mean
run duration, and ΔθT is the angular change
in direction during a tumble. For minicells, the angular change ΔθT is expected to be larger compared to normal cells because
of their smaller body, whereas the run duration τ0 is expected to increase because of their smaller number of flagella.
Indeed, the run duration of minicells was s, compared
with s for normal cells (Figure E). This moderate increase could be well-accounted
for by an effective veto model for bacterial tumbling[46] (Supporting Information). We
also assumed a complete randomization of the swimming direction of
minicells during a tumble (⟨cos(ΔθT)⟩
= 0), in contrast to only a partial reorientation for longer normal
cells (⟨cos(ΔθT)⟩ ≃ 1/2)
as reported previously.[19] Assuming the
biochemical properties of the chemotaxis pathway are unchanged in
the minicells, we predict a chemotactic velocity for the minicells μm/s.
This estimate is in very good
agreement with the experimentally observed value (Figure B), confirming that the difference
in chemotactic ability between normal and minicells is primarily due
to the difference in their physical properties, especially their increased
rotational diffusion coefficient. The model also highlights that,
besides cell propulsion, flagella play another essential role in ensuring
that minicells are capable of chemotaxis, namely, by reducing rotational
diffusion and therefore stabilizing the direction of the minicell
motion. Nevertheless, the model seems to underestimate their chemotaxis
efficiency, which might be either because of the oversimplified model
assumptions or due to the slightly different signaling parameters
of minicells, such as higher concentrations of chemotaxis proteins
or faster signaling due to shorter distances between the chemosensory
complexes and flagellar motors.
Figure 4
Schematics illustrating motility and swimming
parameters of wild-type
cells and minicells. (A, B) Trajectory of a wild-type cell (A) and
a minicell (B), with Dr representing the
rotational diffusion coefficient and τ0 representing
the mean run duration. ΔθT represents the angular
change in direction during a tumble.
Schematics illustrating motility and swimming
parameters of wild-type
cells and minicells. (A, B) Trajectory of a wild-type cell (A) and
a minicell (B), with Dr representing the
rotational diffusion coefficient and τ0 representing
the mean run duration. ΔθT represents the angular
change in direction during a tumble.
Concluding Remarks
Concluding, we observed that E. coli minicells that were engineered to have high levels
of a flagellar gene expression are motile. The swimming pattern of
these minicells was different from that of the parental E.
coli cells, with minicells exhibiting a lower swimming velocity
and directional persistence but increased run duration. These differences
were consistent with the mathematical model describing minicell motility,
and they could be accounted for by their small size and thus faster
rotational diffusion as well as by the smaller number of flagella
per minicell. Despite the potential major impact of these factors
on the bacterial chemotaxis strategy, minicells were capable of following
chemical gradients and accumulating toward sources of chemoattractants.
Given increasing evidence that chemotactic bacteria can follow local
chemical gradients to accumulate toward specific sites within their
animal hosts,[24−26] motility and chemotaxis could therefore be used to
largely enhance the efficiency and specificity of the delivery of
various drugs and protein and nucleic acid effectors that can be carried
by minicells.
Materials and Methods
Strains and Plasmid Construction
The E. coli strain MG1655 was used as the wild-type
for all experiments. A minCDE deletion was conducted
using λ red recombination
relying on pKD46.[48] The kanamycin resistance
cassette was removed using pCP20.[49] pKOV
was used to generate mreBA115V point mutation.[50] Green fluorescent protein (GFP) promoter reporter
for fliC (pAM109)[35,36] was constructed
based on pUA66.[51] pBAD18 or pBAD24 vectors
carrying flhDC genes were used to express FlhDC.[52] sfGFP was expressed using a pTrc99a-backbone-based
vector.
Minicell Production and Purification
For the minicell
production, overnight cultures were inoculated into TB supplemented
with kanamycin and grown at 30 °C with shaking (180 rpm) for
8 h. When necessary, different concentrations of arabinose (0%, 0.001%,
0.01%, 0.1%) were added in the culture to induce FlhDC expression,
and 50 μM isopropyl β-d-1-thiogalactopyranoside
(IPTG) was used to induce the sfGFP expression. For minicell purification,
parental cells were first removed from the cell culture by centrifugation
at 10 000g for 20 min, and minicells were
subsequently harvested by centrifugation at 40 000g for 20 min.
Analysis of Swimming Velocity and Chemotaxis
The average
swimming and chemotactic drift velocity of minicells were measured
as described previously.[35,36,53] Swimming velocity and chemotactic drift velocity of purified minicells
were measured by recording the cell motion in a poly(dimethylsiloxane)
(PDMS) microchamber using phase-contrast microscopy (Nikon TI Eclipse,
10× objective with numerical aperture (NA) = 0.3, CMOS camera
EoSens 4CXP). The cell motion was analyzed as described previously
both via Fourier-based algorithms,[54,55] for measuring
the swimming velocity and chemotactic drift, and cell tracking[53] for measuring mean squared displacements, run
durations, and swimming persistence. A suspension of 100 μM
MeAsp in a tethering buffer (6.15 mM K2HPO4,
3.85 mM KH2PO4, 100 μM ethylenediaminetetraacetic
acid (EDTA), 1 μM l-methionine, 10 mM lactic acid,
pH 7.0) was used to generate a chemical gradient in PDMS chambers.
All data were analyzed using ImageJ (https://imagej.nih.gov/ij/) with custom-written plugins.The chemotactic accumulation
of minicells in response to releasing gradients of MeAsp was measured
with a microfluidic device described previously,[38−40] with a slight
modification. For the microfluidic devices preparation, 0.3% agarose
was added to fill the whole microfluidic chamber. Ten microliters
of tethering buffer each was then added into both source and sink
sides. Afterward, purified minicells were added into the sink pore
and allowed to diffuse into the observation channel for 2 h. A solution
of 2 mM MeAsp was then added to the source pore and allowed to gradually
diffuse through the agarose gel into the observation channel. The
minicell density in the observation channel was monitored over time,
starting immediately after compound addition, using Nikon Ti-E inverted
fluorescence microscope with a 20× objective lens and Lumencor
SOLA-SEII equipped with Andor Zyla sCMOS camera.
Analysis of
Cell-Tracking Data
The mean squared displacement
MSD(t) = ⟨(r(t + t0) – r(t0))2⟩, with r(t0) = (x(t0),y(t0)) the two-dimensional (2D) position of particle i at time t0, was computed as a function
of the lag time t, averaging over particles i and initial times t0. The
MSD was displayed until a lag time of t = 6 s, corresponding
to one-tenth of the duration of the movies (61 s, 2500 frames) and
above which statistics gets poor (less than 10 independent time steps
per average). For the quantification of the tumbling rate and swimming
persistence, trajectories were sorted into swimmer and nonswimmer
based on their radius of gyration as previously described,[53] and these properties were characterized on the
swimmer
trajectories only. Quantification of tumbling rate was also performed
as described previously.[53] For measuring
the swimming persistence, the instantaneous swimming direction was
defined as the 2D instantaneous velocity measured on a 10 frames (0.25
s) wide sliding window normalized to its norm (u(t) = v(t)/|v(t)|). The time autocorrelation
of u(t) was computed by averaging over initial times and swimming cells, .
Quantification of Flagellar
Length and Number of Minicells
Purified minicells were suspended
in a tethering buffer with 10%
glycerol and frozen at −80 °C before analysis by electon
microscopy. For the sample preparation, 5 μL of the minicell
suspension was applied onto hydrophilized carbon-coated copper grids
(400 mesh). After a brief wash with filtered water, bacteria were
stained with 2% uranyl acetate. All samples were analyzed using a
JEOL JEM-2100 transmission electron microscope with an acceleration
voltage of 120 kV. For the image acquisition, an F214 FastScan CCD
camera (TVIPS; Gauting) was used. The flagellar number and length
of minicells were quantified manually with ImageJ.
Promoter Activity
Analysis
The activity of the gfp reporter
of the fliC promoter was assayed
using a BD LSRFortessa SORP cell analyzer (BD Biosciences) as described
previously.[35,36]
Authors: L G Wilson; V A Martinez; J Schwarz-Linek; J Tailleur; G Bryant; P N Pusey; W C K Poon Journal: Phys Rev Lett Date: 2011-01-05 Impact factor: 9.161
Authors: Jun Liu; Bo Hu; Dustin R Morado; Sneha Jani; Michael D Manson; William Margolin Journal: Proc Natl Acad Sci U S A Date: 2012-05-03 Impact factor: 11.205