Single-Cell Census of Mechanosensitive Channels in
Maja Bialecka-Fornal1., Heun Jin Lee2., Hannah A. DeBerg3, Chris S. Gandhi4, Rob Phillips1,2,5*
1Biochemistry and Molecular Biophysics Option, California Institute of Technology, Pasadena, California, United States of America, 2Department of Applied Physics,
California Institute of Technology, Pasadena, California, United States of America, 3Department of Physics and the Center for Physics of Living Cells, University of Illinois at
Urbana-Champaign, Urbana, Illinois, United States of America, 4Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California,
United States of America, 5Division of Biology, California Institute of Technology, Pasadena, California, United States of America
Bacteria are subjected to a host of different environmental stresses. One such insult occurs when cells encounter changes in
the osmolarity of the surrounding media resulting in an osmotic shock. In recent years, a great deal has been learned about
mechanosensitive (MS) channels which are thought to provide osmoprotection in these circumstances by opening
emergency release valves in response to membrane tension. However, even the most elementary physiological parameters
such as the number of MS channels per cell, how MS channel expression levels influence the physiological response of the
cells, and how this mean number of channels varies from cell to cell remain unanswered. In this paper, we make a detailed
quantitative study of the expression of the mechanosensitive channel of large conductance (MscL) in different media and at
various stages in the growth history of bacterial cultures. Using both quantitative fluorescence microscopy and quantitative
Western blots our study complements earlier electrophysiology-based estimates and results in the following key insights: i)
the mean number of channels per cell is much higher than previously estimated, ii) measurement of the single-cell
distributions of such channels reveals marked variability from cell to cell and iii) the mean number of channels varies under
different environmental conditions. The regulation of MscL expression displays rich behaviors that depend strongly on
culturing conditions and stress factors, which may give clues to the physiological role of MscL. The number of stress-
induced MscL channels and the associated variability have far reaching implications for the in vivo response of the channels
and for modeling of this response. As shown by numerous biophysical models, both the number of such channels and their
variability can impact many physiological processes including osmoprotection, channel gating probability, and channel
Citation: Bialecka-Fornal M, Lee HJ, DeBerg HA, Gandhi CS, Phillips R (2012) Single-Cell Census of Mechanosensitive Channels in Living Bacteria. PLoS ONE 7(3):
Editor: Arnold Driessen, University of Groningen, Netherlands
Received August 5, 2011; Accepted February 9, 2012; Published March 13, 2012
Copyright: ? 2012 Bialecka-Fornal et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: RP, MBF, and HJL were supported by National Institutes of Health (NIH) grant R01 GM084211 and NIH Director’s Pioneer Award grant DP1 OD000217.
MBF was supported by a Caltech Provost’s office fellowship. HAD was supported by a National Science Foundation graduate research fellowship and the
physiology course at the Marine Biology Laboratory in Woods Hole, Massachusetts. CSG was supported by NIH grant R01 GM084211. The funders had no role in
study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: firstname.lastname@example.org
. These authors contributed equally to this work.
The connection between structure and function is one of the key
tenets of modern biology. However, structure alone cannot explain
the physiological workings of a given organism. A more nuanced
view takes into account the single-cell numbers, stoichiometry, and
population distribution of the various molecules that partake in the
life processes of an organism. As a result of this challenge, recent
years have seen a number of careful studies aimed at establishing
the census of the molecular actors in a host of different situations.
Examples include the distribution of metabolites in bacteria ,
the distribution of proteins related to the actin cytoskeleton ,
counts of the proteins involved in glycolysis in yeast  and the
stoichiometry of proteins associated with adhesion complexes .
Similar studies have been made that attempt to provide a genome-
wide snapshot of the distribution of mRNAs or proteins (or in
some cases both) [5,6,7,8,9]. This partial accounting only scratches
the surface of efforts currently underway to measure the number of
molecules present in a cell at different stages in the cell cycle and in
response to various environmental insults. To date, this kind of
molecular census taking has yet to be performed on proteins
related to mechanosensation.
Mechanosensation is a key biological process found across all
domains of life and over a wide range of spatial and energy scales
. One important case study in mechanosensation is provided
by mechanosensitive channels in bacteria . One of them, the
mechanosensitive channel of large conductance (MscL), has been
studied extensively, both using crystallography to provide
structural snap shots [12,13] and single-channel recordings to
measure the gating properties of this channel [14,15]. Despite
these numerous studies, the in vivo characterization of MscL
expression levels under physiological conditions remains relatively
limited. In previous work, it was found that the relative mean
abundance of mechanosensitive channels increased under stress
conditions such as starvation and high media osmolality . We
set out to undertake a molecular census of MscL channels
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expressed in single Escherichia coli cells under various growth and
stress conditions with an absolute number calibration. We also
sought to measure the cell to cell variability and to assign
functional forms to the population distributions.
The absolute mean number of channels is a vital ‘‘conversion’’
parameter which can bridge the single-molecule level understand-
ing resulting from electrophysiological measurements, X-ray
structures and biophysical models to the ensemble phenotypic
behavior of MscL. Single-channel electrophysiology provides the
single-channel conductance of an open MscL channel and the
probability that the channel is open under any given tension, but
these data have rarely been translated into the behavior in the cell.
The mean number of channels per cell, in principle, allows an
extrapolation of the single channel results to a whole cell (with
certain exceptions noted below) and can determine the total
number of channels open and how much total transport occurs.
That is, a proper molecular census can make single-molecule
results relevant to the cellular scale. We note, however, there are
instances of MscL mutant channels that exhibit behavior in
electrophysiology that are different from the properties expected
from cell-based assays [17,18].
A paradigmatic view of these channels is that they serve as
osmotic relief valves when microbes are subjected to osmotic shock
[15,19]. Currently, it is unclear just how many channels are
needed for osmotic protection or how much total water transport
occurs during osmotic shock. Biophysical models [20,21] that
estimate the magnitude of these effects depend on the mean
number of channels and can vary according to the assumed
expression level. Another interesting biophysical example is related
to cooperative gating  and clustering [22,23] where each
phenomenon is predicted to be strongly dependent on the areal
density of channels.
Previous estimates of the number of channels per cell were
based on radio-labeling of purified membrane fractions  or
[11,16,25] and are not truly, or at least directly, in vivo. They
can be affected by assumptions of the reconstituted protein
density, geometric scaling of the patch, and/or number of cells
needed to form a spheroplast. These results are summarized in
Table 1, showing a range of 4 to 100 conducting channels per cell.
The uncertainty of these estimates prevents us from quantitatively
relating the single-molecule and phenotypic pictures and, as such,
motivates a more definitive measurement. Further, these assays, at
best, can estimate the total number of active channels. We do not
know how many channels are inactive or have been inactivated,
either in vivo and/or after preparation for in vitro measurements. In
this work we present an absolute MscL census in vivo, which
eliminates uncertainties related to reconstitution and paves the
way for a measurement of the total number of channels, both
active and inactive.
on giant spheroplasts
Additionally, the mean number of channels may change with
growth conditions. We postulate that shifts in the population
census in response to environmental factors yields an improved
contextual understanding of the physiological role of MscL and the
factors that control its induction and regulation. Previous work
 found that production of MS channels is induced by entry
into stationary phase or by growth in a media supplemented with
NaCl to increase its osmolality. These studies also demonstrated
that MscL expression is enhanced by the production of the sigma
factor RpoS (also known as ss), the primary sigma factor
controlling regulation during stress response or in preparation
for stationary phase . There are numerous types of stress
responses associated with RpoS , well beyond the scope of this
work to consider in a comprehensive way. However, one
particularly intriguing response is related to the carbon source of
the media. Media associated with slower growth rates have been
observed to induce elevated RpoS levels [28,29,30]. Thus,
different types of culture media may offer a means of inducing
different levels of RpoS and associating MscL with functions other
than osmotic protection. As a result, we examine the expression
levels of MscL and RpoS in three common media with
progressively slower growth rates: the Miller variant of LB media
with 10 g/L NaCl (LB-Miller) , M9 minimal media
supplemented with glucose (M9+glucose), and M9 media supple-
mented with glycerol (M9+glycerol). We also measure the cell-to-
cell variability in expression level. The population distribution of
the number of protein subunits is a quantity of great interest and
recent insights [32,33,34,35,36] make it possible to relate the
characteristics of a distribution to the ‘‘noise’’ associated with the
processes of both transcription and translation, which, in turn,
provides a means of probing the underlying regulatory architec-
Our approach presented in this study is complementary to
earlier electrophysiological studies. We measure the mean number
of MscL channels per cell under various culturing conditions using
quantitative Western blots and single-molecule calibrated fluores-
cence microscopy. Further, by measuring the fluorescence of
thousands of individual cells expressing chromosomally-integrated
MscL fluorescent protein fusions, we determine not only the mean
number of channels per cell, but also the cell-to-cell variability.
To carry out the measurements described above, two
independent techniques were employed. We used fluorescence
microscopy to measure the distribution of MscL-sfGFP expression
levels across a population of cells subjected to different growth and
stress conditions. In parallel, we performed a series of bulk assays
using quantitative Western blots to compare the mean expression
levels of MscL-sfGFP to wild-type MscL to ensure that the GFP
fusion does not alter native expression levels.
Confirming Native Expression and Proper Function of
MscL-sfGFP Fusion Proteins
MscL-fluorescent protein fusions have been previously ex-
pressed in E. coli using exogenous plasmids with inducible
promoters . However, our experiments require MscL fusion
proteins produced at native levels, where the expression level is
controlled by the endogenous MscL regulatory system. To
accomplish this, we replaced the native MscL coding region of a
wild-type E. coli strain (MG1655) with a sequence that coded for
MscL fused to super-folder green fluorescent protein (sfGFP) 
(see Chromosomal Integration in Materials and Methods), creating the
MscL-sfGFP fusion expressing strain MLG910. To compare the
Table 1. Summary of reports on the number of MscL
channels per E. coli cell.
Number per CellMethodReference
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expression levels between the MLG910 and MG1655 strains, we
performed a series of quantitative Western blots. The expression
levels for the two strains were comparable and in many conditions,
within the accuracy of our technique (see below MscL Channel
Counts with Quantitative Western Blots for details).
To establish the gating functionality of our fusion, we integrated
the coding region of MscL-sfGFP into the osmotically susceptible
MJF612 strain (a generous gift of Ian Booth), which had four
mechanosensitive channel genes (DmscL, DmscS, DmscK, and DybdG)
 knocked out. We performed a series of osmotic shock
survivability assays (see Plaque/Survivability Assays in Supporting
Information S1 for details). We observed a considerably higher
survival rate (Figure S1) for cells expressing our fusion (71613%
for 0.5 M NaCl osmotic shock) as compared to the rate from the
MJF612 strain (15% for 0.5 M NaCl osmotic shock), but a lower
survival rate as compared to that from the WT strain MG1655
(defined as 100%). For comparison, the work of Levina et. al
reported a survival rate difference of ,10% between a similar WT
(Frag1) and mutant strain (MJF429) . Part of this discrepancy
may be explained by the exact choice of protocol. We have
observed that survival rates can be systematically influenced by
factors other than the functionality of the channel, for example,
speed of mixing and choice of media. To directly measure channel
activity, it has been shown that spheroplasts made from the
MLG910 strain demonstrate electrophysiological activity of MscL-
sfGFP which is nearly identical to that of WT MscL (unpublished
data, A. Rasmussen and I.R. Booth). Taken together, these results
suggest the MscL-sfGFP fusion is functionally similar to WT
MscL. We also used fluorescence microscopy to check for the
proper insertion of MscL in the cell membrane. For a limited set of
data, we used confocal microscopy and fluorescence recovery after
photobleaching (FRAP)  to determine that the majority of the
fusion proteins are mobile in the membrane (Figure S2). We
interpret all these findings as an indication that the MLG910
fusion strain is a fair representation of the wild-type MG1655
MscL Channel Count with Quantitative Western Blots
To establish the impact of stress factors on the expression levels
of MscL, we used quantitative Western blots. We prepared lysates
derived from the various strains, grown in three different media to
early exponential (OD6000.3) and stationary phase (OD6001.2–
1.7). Known volumes of lysates were run alongside purified protein
references (either MscL or MscL-sfGFP) of known concentration.
The references were diluted in MJF612 lysate to keep the total
non-specific protein loaded similar to the whole cell lysates.
Reference proteins and lysates were separated by SDS PAGE,
transferred to nitrocellulose membranes, and immuno-stained with
primary antibodies for either MscL or GFP (as discussed below).
Detection of the bands was achieved by imaging the chemilumi-
nescence resulting from horseradish peroxidase (HRP) labeled
secondary antibodies. By measuring the relative intensity of the
bands and comparing them to the purified protein reference
bands, we determined the mean number of channels per cell for a
given condition (see Western Blots in Materials and Methods for
For the MG1665 strains, we used a polyclonal antibody for
MscL (a generous gift of S. Sukharev), which showed multiple
bands in every lane (Figure 1A), presumably due to the polyclonal
nature of the antibody. We were able to identify the specifically
labeled MscL bands (15 kDa) from the nonspecifically labeled
bands (see Western Blots in Materials and Methods for details). The
MscL-sfGFP fusion protein is ,43 kDa, which overlaps with some
of the nonspecific bands of the MscL antibody. Accordingly, to
accurately measure the expression of MscL-sfGFP in the MLG910
strain, we used a monoclonal GFP antibody which displayed
higher specificity towards the MscL-sfGFP fusion protein
(Figure 1B). As an additional consistency check, we measured
the expression levels of MscL-sfGFP in the MLG910 strains using
the MscL antibody and found comparable results (see Figure S3
The Western blot measurements showed much higher MscL
expression levels, as compared to previously published results
(Table 1). In LB-Miller medium, we did not observe a resolvable
change in MscL levels with increasing age of the culture (OD600)
(lanes 9 and 12 of Figures 1A and 1B). However, in the slower
growth-rate M9-based media, the number of MscL channels per
cell increased by nearly 2-to-3 fold during the transition period
from exponential to stationary growth phase (lanes 7 and 8 vs. 10
and 11 in Figures 1A and 1B), similar to previous findings . To
slow the growth rate and increase the potential stress created by
our M9 media, we omitted optional supplements (thiamine,
Casamino acids, and riboflavin) typically used to increase the
growth rate. In addition, we used two different carbon sources,
glucose and glycerol, where the nutritionally poorer glycerol
reduced the growth rate by a factor of two or more, depending on
the culture conditions. These results demonstrate that the carbon
source and associated growth rate influence the amount of
upregulation of MscL during the transition from exponential to
stationary growth phase.
When cells are in late exponential phase or subjected to
environmental stresses, an alternative sigma factor known as RpoS
is activated . Earlier work has examined how the expression of
mechanosensitive channels is affected by RpoS expression 
and we have explored this as well. We measured the level of MscL-
sfGFP protein in the MLG910 strain where the rpoS gene had been
knocked out (MLG910-DrpoS). As expected , the expression of
MscL-sfGFP protein in the MLG910-DrpoS strain was significantly
lower (Figure 1C, lanes 6-11). In contrast to the previous results for
the MG1655 and MLG910 strains, we observed neither an
increase in channel expression upon entry into stationary phase
nor a change in expression level due to different carbon sources, as
previously noted . We take these results to suggest that MscL
expression in the DrpoS strain represents the baseline level of MscL
expression in the absence of any stress.
Next, we performed a relative-comparison Western blot for the
MG1655 and MLG910 strains with antibodies for RpoS
(Figure 1D), where all lanes were normalized to lane 11 (the
MG1655 strain grown in M9+glucose media). To ensure
consistency, the RpoS blot used aliquots from the same lysates
used in Figures 1A and 1B. In LB-Miller media we observed that
RpoS levels were nearly absent or relatively low for cells in
exponential phase (Figure 1D, lanes 9 and 12) as compared to
those found in stationary phase (Figure 1D, lanes 3 and 6), as
previously reported . For cells grown to exponential phase in
M9+glucose and M9+glycerol, there were noticeable levels of
RpoS present (Figure 1D, lanes 7, 8, 10 and 11), consistent with
previous results [28,29,30]. In this context, we can interpret the
up-regulation of MscL, at least in M9 media, as a response to
carbon source related stress. In stationary phase, we observed
media-dependent changes in RpoS expression levels. For cultures
grown in LB-Miller, there was a dramatic 40-fold or greater
upregulation of RpoS levels (Figure 1D, lanes 3 and 6 vs. 9 and
12). For three conditions in minimal media (Figure 1D, lanes 1, 2,
and 5 vs. lanes 7, 8, and 11), the measured levels of Rpos showed
more modest changes, decreasing by 1.2–1.9 fold. The remaining
condition in minimal media, MG1655 grown in M9+glycerol,
showed an inconsistent trend (Fig. 1D lanes 4 vs. 10) of increasing
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RpoS levels. We note that interpretation of these results can be
complicated by native proteolysis of RpoS, which depends on the
growth media and growth phase, leading to substantial variability
of the RpoS protein half-life ranging from 1 minute to over
30 minutes [28,29,30,41].
MscL Channel Count with Fluorescence Microscopy
To conduct a single-cell based census of MscL channels, we
MLG910 strain under various growth conditions and stages. We
imaged multiple fields of view, typically analyzing .1000
immobilized bacterial cells per condition. Under most conditions
(except where noted), we observed a dynamic, somewhat grainy
distribution of fluorescence primarily localized along the entire cell
perimeter with no strong preference for the poles of the cell (see
Figure 2 for representative images), which appears to be in
contrast to previous findings . Occasionally, we observe there
are mobile puncta (1,3 per cell), where each punctum contains
less than 5% of the total integrated fluorescence from the cell.
These puncta do not show a preference for the cell poles.
However, for cells grown to stationary phase or in media
supplemented with excess salt (500 mM NaCl), less than 5% of
the cells exhibit static, nearly diffraction-limited punctate features,
typically found at one pole. The total integrated number of
fluorescence counts of each cell was determined and converted
into the total number of fully assembled channels by using a
calibration factor of fluorescence-counts-per-sfGFP (see Single
Molecule Fluorescence Calibration in Materials and Methods for
details), explicitly assuming the fluorescence of each sfGFP
represents a single channel subunit and that five subunits form a
fully assembled channel [12,43].
In agreement with the quantitative Western blots, these
measurements indicated that the media and the age of the culture
affected the expression level of MscL-sfGFP (Figure 3). The
fluorescence microscopy measurements indicated that the mean
number of channels per cell determined by total integrated
fluorescence is on the order of 300–1400 (102to 103channels per
mm2), depending on culturing conditions.
The number of channels increased in M9 minimal media as
compared to cells grown in LB-Miller media (Figures 3A and 3B
compared to 3C). Depending on the carbon source, there was a
2.5-fold (M9+glycerol) or a 1.5-fold (M9+glucose) increase in the
Figure 1. Representative Western blots showing expression of MscL, MscL-sfGFP, and RpoS. Arrows indicate the protein of interest.
Other bands are the result of non-specific binding. The strains of interest were cultured to exponential (exp) and stationary (stat) phase in LB-Miller
(LB), M9+glucose (U), and M9+glycerol (Y). In Figures 1A, 1B, and 1C lanes 1 through 5 are a concentration series of a known number of purified
channels diluted into lysate from the MJF612 strain (References). The numbers under lanes 6 through 12 represent the average number of channels
from three independent Western blots for the respective conditions. The total error of each measurement includes contributions from the standard
deviation of 3 repetitions and the systematic uncertainties in the absolute calibration related to chemiluminescence linearity, initial cell culture
density, and lysis efficiency. (A) Western blot performed with MscL antibodies. Lysate from the MJF612 strain (612) was used as a negative control
(lane 6). Lanes 7 through 12 show the MscL levels in the MG1655 strain (WT). (B) Western blot performed with GFP antibodies. Lysate from the
MJF612 strain (612) was used as a negative control (lane 6). Lanes 7 through 12 show the MscL-sfGFP levels in the MLG910 strain (MLG). (C) Western
blot performed with GFP antibodies. Lysate from MJF612 strain (612) was used as a negative control (lane 12). Lanes 6 to 11 show the MscL-sfGFP
levels in the MLG910-DrpoS strain (DR). (D) Western blot performed with RpoS antibodies. Lysate from the MLG910-DrpoS strain (DR) was used as a
negative control (lane 13). Lanes 1 to 12 show the RpoS levels in the MLG910 (MLG) and MG1655 (WT) strains. The numbers under the lanes are the
relative amount of RpoS, as compared to the lysate from M9+glucose (lane 11), determined by the average of three independent repetitions. The
errors are the standard deviation.
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number of MscL-sfGFP channels per cell in the early exponential
phase of growth. Interestingly, as the M9-media-grown cells
entered stationary phase, they reached similar expression levels for
both carbon sources (Figure 3D).
We also observed that the number of channels per cell increased
steadily with salt concentration (Figure 3E), presumably demon-
strating osmotic induction  related to the increased osmolality
(mOsm/kg) of the media (Table S1). During exponential phase,
cells grown in the various salt-supplemented M9 media -
M9+glucose+100 mMNaCl (342 m
se+250 mM NaCl (529 mOsm/kg) and M9+glucose+500 mM
NaCl (886 mOsm/kg) - showed a 2–3 fold increase in protein
expression, as compared to cells grown in M9 media without
supplemented salt (234 mOsm/kg). Cells grown to stationary
phase in the various salt-supplemented media appear to be
approaching a common expression level of ,1300 channels per
cell, nearly twice the maximum level seen in M9 media without
salt (,700 channels per cell).
The age of the culture (OD600) also influenced the mean
number of MscL proteins per cell. In the presence of 100 mM or
250 mM NaCl salt, the cells showed a characteristic increase in
expression level around OD600<1, which can be interpreted as
arising from the stress associated with transition to stationary
phase. However, cells grown in the presence of 500 mM NaCl did
not show this tendency. Instead, we observed a fairly-constant,
relatively-high level of expression, which may represent a
maximum level of MscL expression in response to salt and growth.
To summarize, the results from both experimental methods
showed a general trend of increasing MscL levels as the quality of
the media’s carbon source was decreased, in going from LB-Miller
to M9+glycerol, and as the cultures entered stationary phase. The
agreement between the mean values found from fluorescence
microscopy and quantitative Western blots is summarized in
Distribution of MscL Subunits in a Population
In addition to measuring the mean number of fully-assembled
channels, Nmean, we used the fluorescence dataset to determine the
population distribution of MscL monomer subunits expressed
under various growth and stress conditions (see Single Cell
Fluorescence Microscopy in Materials and Methods for details). Not
only are such measurements a first step towards addressing the
important question of the cell-to-cell variability of these channels
in living bacteria, but they also provide insights into the largely
unexplored nature of the regulation of these channels under
different physiological conditions. Under different conditions, we
observed changes in the width and shape of the respective protein
distributions (Figure 4). Though earlier work has given snapshots
of the expression level distributions of other proteins in cells
[5,6,8], the kind of systematic analysis as a function of both growth
media and OD done here provides further clues as to additional
physiological roles that these channels might play as well as into
the detailed nature of their regulation which until now remains
completely unclear. To characterize the distribution widths, we
determined the standard deviation, s, and Fano factor (bFano) for
each distribution, where bFanois given by
The Fano factor is a measure of the non-Poissonian character of
the distribution, where a Poisson distributed protein abundance
would correspond to bFano=1. The MLG910-DrpoS strain did not
show a wide variation in the Fano factor value with increasing
OD600(Figure 4A and Table S2). We interpret these Fano factor
values as the baseline level of population variability in the absence
of carbon source or salt associated stress. There was a dramatic
increase in the Fano factor of the RpoS-expressing MLG910 strain
distributions, as compared to the MLG910-DrpoS strain (Figure 4B
and Table S2).
The presence of RpoS alone caused a 10-fold increase in the
Fano factor value. In the presence of 250 mM NaCl, an even
larger 10–30 fold increase was observed (Figure 4C and Table S2).
This increase depended on the OD600of the culture, indicating
that the presence of salt introduced further changes in the
expression profile. The results for all the tested conditions are
summarized in Table S2.
Numerous theoretical models have linked the steady-state, gene-
expression distribution of a population to stochastic factors
describing the transcriptional and translational processes of a
single cell. One of the simplest descriptions results in a steady-state
distribution described by a gamma distribution of the form
where p(x) is the probability of occurrence of x protein subunits, a
is a measure of the rate of transcriptional bursts, and b is the
measure of size of the corresponding translational burst . For
this class of models b=bFano. We fit this distribution to our data as
a crude gauge of the complexity of MscL regulation. For the cells
expressing RpoS, we observed an increasing trend of both the a
and b parameters with growth phase, and/or salt levels (Table S2).
In general, the distributions were reasonably described by such a
Figure 2. Typical fluorescence microscopy images of MLG910
for various conditions. The white scale bar is 2 mm long. The relative
contrast of the individual images has been unaltered. The contrast of
the overall composite image has been adjusted for clarity.
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fit in early exponential phase, but outside this phase or in the
presence of salt, the gamma distribution did not account well for
our data (last two panels of Figure 4C).
Two Independent Methods Lead to Higher Than
Expected MscL Expression Levels
In this work, we present a robust approach to counting the
absolute number of MscL channels and studying the changes in its
expression caused by various stress factors. The strategy is general
enough to be applied to other membrane proteins. We use two
independent methods: quantitative Western blots for bulk
measurement and fluorescence microscopy for measurement at
the single cell level. Both methods obtained comparable results,
showing somewhat similar numbers of channels and the same
general expression trends with media choice and growth phase
(Table 2). Together, these techniques provide a much more
convincing picture. As an additional consistency check, we note
that our relative expression level changes associated with carbon
source, growth phase and osmolality for each method are of a
similar scale to those previously reported . These observations
suggest that the absolute numbers of MscL channels measured in
our study are a representative in vivo census, with certain
exceptions detailed below.
Both methods have their associated systematic uncertainties.
For example, quantitative Western blots may be affected by
incomplete protein extraction or proteolysis that may occur during
lysate preparation (see Lysate Preparation in Materials and Methods
for details). In the case of fluorescence microscopy, photobleach-
ing, misfolding  , lack of maturation , or self-quenching of
sfGFP molecules will lead to a systematic reduction of total
fluorescence. For example, homo-polar excitation transfer (self-
quenching) may be expected when sfGFP molecules are roughly
within one Forster radius, as may be the case when MscL-sfGFP is
in pentameric form or when clusters are formed. Based on our
observations (see MscL Channel Count with Fluorescence Microscopy in
Results), we expect most of the channels will not be in clusters. If
Figure 3. Mean channel counts per cell determined by fluorescence microscopy (FM) for various media versus OD600. (A) M9+glycerol.
Fusion strains with (MLG910, light blue squares) and without RpoS (MLG-DrpoS, yellow squares). (B) M9+glucose. Fusion strains with (MLG910, green
squares) and without RpoS (MLG-DrpoS, red squares). (C) LB-Miller. Fusion strains with RpoS (MLG910, black squares). In Figures 3A, 3B, and 3C, the
corresponding mean number of channels determined by Western blots (WB) for the MLG910 strain (open squares) and the MG1655 strain (open
triangles) are shown for reference. (D) Comparison of fluorescence microscopy results from MLG910 grown in three different media. (E) Comparison
of fluorescence microscopy results from MLG910 grown in M9+glucose supplemented with four different NaCl concentrations: 0 mM (green squares),
100 mM (dark blue squares), 250 mM (gray-blue squares), and 500 mM (dark gray squares). The error bar of each fluorescence microscopy results
measurement is dominated by systematic uncertainties in the absolute calibration related to single-molecule fluorescence calibration. The standard
error of the mean of the uncalibrated fluorescence counts per cell is typically less than 5% of the total error bar.
Single-Cell Census of Mechanosensitive Channels
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self quenching occurs, the effect will primarily affect the
pentameric form of MscL-sfGFP. The total fluorescence of a
pentamer will be less than the fluorescence of five well separated
monomers. With these considerations in mind, even after
controlling for many of these factors, each method likely results
in an undercount. However, our results still indicate that the
total absolute number of MscL proteins per cell is at least an
order of magnitude higher than previously reported numbers
Induction of MscL Expression Is Not Described Well by a
Simple Biophysical Model
To our knowledge, we are the first to measure the cell-to-cell
variability of MscL expression, which varies substantially with
Table 2. Comparison of channel counts per cell from quantitative Western blots and fluorescent microscopy.
Condition Western blot Fluorescence Microscopy
StrainMediaGrowth Phase OD600
MG1655 LB-MillerExponential 0.34806103a
Exponential 0.3 3646102a
MLG910LB-Miller Exponential 0.35316313b
MLG910 Exponential0.31 4216166b
MG1655 LB-MillerStationary1.78 544692a
MLG910 LB-Miller Stationary1.723166124b
MLG910 Stationary 1.174826131b
aWestern blots performed with MscL antibody.
bWestern blots performed with GFP antibody.
MG1655 and MLG910 were cultured in LB-Miller media (LB), M9 minimal media supplemented with glucose (U), and M9 minimal media supplemented with glycerol (Y)
to the indicated optical density (OD600).
Figure 4. Distribution of MscL Subunits under Different Growth Conditions at Various Stages of Growth. The red curves show the
fitting of the gamma distribution to the histograms. The OD600and the Fano factor bFanofor a given sample are listed. (A) MLG910-DrpoS strain
grown in M9+glucose to OD 0.46, 0.81, and 1.18, respectively. (B) MLG910 strain grown in M9+glucose to OD 0.3, 0.67, and 1.23, respectively. (C)
MLG910 strain grown in M9+glucose+0.5 M NaCl to OD 0.26, 0.71, and 1.2, respectively.
Single-Cell Census of Mechanosensitive Channels
PLoS ONE | www.plosone.org7March 2012 | Volume 7 | Issue 3 | e33077
culturing conditions. In this work we describe these changes
quantitatively by determining the Fano factor empirically from the
distributions and by fitting a gamma distribution to the histograms
of MscL monomers at the single cell level (red curves of Figure 4
and parameters listed in Table S2). The gamma distribution is
derived from a model which assumes: the mRNA expression level
is determined by a single-state, unregulated promoter; the proteins
are expressed in translational bursts from a single copy of mRNA;
the number of proteins per burst event is described by an
exponential distribution; and the translation events are uncorre-
lated in time. There is no transcriptional ‘‘feedback’’ such as auto-
regulation or regulation by another gene. The rate of translation is
a constant. This distribution accurately describes the measured
expression levels of a few simple model genetic circuits in E. coli
[46,47]. For low stress conditions (exponential phase and/or
media without supplemented salt), the gamma distribution
represent the data well. In stationary phase, when significant
regulation by RpoS occurs, or in the presence of salt, when
osmotic induction occurs, the gamma distribution does not
provide a good fit for our data. This suggests that a simple
single-promoter state model of transcription  may not be
adequate to quantitatively describe the observed increase in MscL
expression under these conditions. We must bear in mind that the
conditions leading to the derivation of model distributions make
specific assumptions about both transcription and translation that
may not be satisfied in the context of these genes. For example,
distributions more complicated than the gamma distribution can
arise when there is a multiple-state promoter or multiple
promoters involved . Further, the regulatory behavior of
RpoS introduces another layer of complexity not considered in
these models. It may not even be possible to distinguish between
different biophysical models solely on the basis of fitting calculated
distributions to measured steady-state protein distributions .
As a result, it is really only as a point of departure that we make
preliminary fits to our data in terms of gamma distributions,
knowing full well that the situation can be (and is) more
complicated. In many ways, our thinking is analogous to that
used when Hill functions are used to fit binding data since such fits
can provide a convenient summary of large quantities of data 
without necessarily reflecting any underlying mechanistic picture
of the binding process.
Osmotic and Carbon Source Induction Mechanisms
Produce Comparable MscL Expression Levels
The results summarized in Figure 3E reconfirm earlier findings
that demonstrate MscL levels can be raised by increasing the salt
of a given culture media . One explanation of this trend is that
the cells are responding to the increased osmolality of the media
and preparing for a possible hypo-osmotic shock. For comparison,
it is interesting to consider the amount of induction caused by a
poor carbon source (Figure 3A vs. 3E). For example, the levels of
MscL present in the MLG910 strain grown in M9+glycerol
(277 mOsm/kg) are comparable to those found in M9+gluco-
se+100 mM NaCl (342 mOsm/kg), where the growth rates in
both media are similar, and within ,20% of those found in
M9+glucose+250 mM NaCl (529 mOsm/kg). This would imply
that carbon source induction mechanisms are, at least, on a
comparable scale to salt induction related ones. It is unclear if the
response to carbon source related stress has a specific physiological
purpose or if it is a passive response. In previous work , it was
found that some of the genes that were up-regulated during
starvation conditions were associated with metabolism and
transport. However, the same study also noted many of the
upregulated genes were not associated to any specific response.
RpoS Expression Level is Not the Only Factor Impacting
We find that the presence of RpoS leads to much higher
channel counts in RpoS expressing strains than in the MLG-DrpoS
mutant (Figs. 3A, 3B, and 4A vs. 4B) thus confirming RpoS plays
an important role in MscL regulation . The effect that a given
level of RpoS protein has on regulation depends on how many of
the RpoS subunits assemble into full RNAP-RpoS holoenzymes.
The RNAP-RpoS regulatory network is governed by multiple
factors which lead to a complex, shifting balance between
production, inhibition, and proteolysis [28,52,53]. Thus, it can
be difficult to establish a clear quantitative relationship between
RpoS and MscL levels. For example, cells grown to stationary
phase in LB-Miller showed the highest levels of RpoS by far (4-fold
or higher), although the levels of MscL were roughly half of those
found in cells grown to stationary phase in minimal media. In this
case, it is possible that a sizeable fraction of the RpoS subunits are
prevented from forming RNAP-RpoS holoenzymes by anti-sigma
factors and/or other proteins that act like anti-sigma factors, such
as RssB [41,54,55,56]. While it is also possible that the accuracy of
our RpoS measurements is affected by the considerable variation
in turnover for RpoS [28,29,30], it does appear, nonetheless, there
are factors other than the absolute level of RpoS required to
RpoS, there are other means of MscL induction. We observed the
salt dependent upregulation of channels in the MLG910-DrpoS
strain (Figure S4), as has been previously noted .
Implications for Electrophysiology
There is a considerable discrepancy between our measured total
number of channels and the reported number of active channels
from the work summarized in Table 1. One possibility is that
experimental uncertainties and variations in cell culture conditions
may have created this artificial divide. Another distinct possibility
is that the vast number of channels we observe are inactive. From
our FRAP studies (Figure S2) and Western blots performed on the
cytoplasmic fraction of cell lysate, we estimate less than 10% of the
total observed MscL is found in the cytoplasm and the remainder
should be in the cell membrane. If the inactive fraction of proteins
occurs in vivo, it may be caused by improper assembly (e.g.
incorrect stoichiometry or misfolding), improper insertion, or
inactivation (i.e., by tension). On the other hand, it is also possible
that proteins are inactivated during in vitro sample preparation
prior to electrophysiological measurements, notably the require-
ment to produce large spheroplasts amenable to patch clamp
experiments. Finally, since MscL channels gate at tensions near
the point of membrane rupture, an underestimation of the total
number of channels can occur if the patch breaks before reaching
saturating tensions. A possible test of these ideas would be to apply
the quantitative fluorescence techniques demonstrated in this
current work to an electrophysiological setting. The total number
of fluorescently tagged proteins within a patch or spheroplast could
be measured and compared with the number of electrophysiolog-
A Multitude of MscL Channels Can Impact Gating Activity
At this time, it is unclear what fraction of channels we observe in
vivo is active. Given the relatively large number of channels we
observe (Ntotal<300–1000), it is interesting to speculate on how
these numbers might impact channel gating behavior, if we
assume all the channels are active.
For example, channel activity in vivo may occur at lower tensions
than might be expected. As a simple illustration of this effect,
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we calculate the average number of open channels, Nopen,
where popenis the probability of a channel being open, t is the
applied tension, DA is the area difference between open and closed
state, and Eopenand Eclosedare the energies of the open and closed
state, respectively . From this expression, we find the critical
tension, tc, required to open one channel on average (i.e. when
What this expression shows is that by having multiple channels
present, the tension needed to open at least one channel is reduced
(Figure 5). There is an effective lowering of the gating energy (Eopen
- Eclosed) by ln(Ntotal)/b=5,7 kBT. The tension requirement for
gating one channel (or very few) can be considerably lower than
t1/2, the tension where Popen=0.5 (dashed lines of Figure 5). It is
commonly noted that the value of t1/2, determined from
electrophysiological measurements, is very close to the tension
when a typical membrane ruptures in the range between 1 and
3 kBT/nm2. By having several hundred channels, a bacterium
may only need to activate a small percentage of channels, rather
than half, thus operating in tension ranges below lytic values.
Also, recent work has predicted that at sufficiently high protein
areal-densities, channels can demonstrate cooperative gating .
In the range below ,1023channels per mm2, channels essentially
gate independently of each other. However, for our measured
values, 102–103channels per mm2, the probability of two channels
opening at-a-time can be equal to or even greater than the
probability of one channel opening as the applied tension is
increased to values approaching t1/2.
Nopen=1) is tc~
Relevancy to Osmotic Protection and Survivability
Currently, there are two analytically modeled mechanisms for
mechanosensitive channels to protect the cell membrane from
rupture: transport of water and/or osmolytes which is mediated by
conductance through open channels [20,21] and expansion of
non-conductive MscL proteins  which adds extra area to the
membrane. Both types of models predict greater protection with
greater numbers of channels.
As a numerical example, previous work  has estimated that
the membrane tension experienced by a bacterium-sized vesicle
under a potentially-lethal osmotic shock (,300 mOsm) can be
effectively reduced below lytic levels if the number of activatable
MscL proteins exceeds ,100. We are, for the moment, neglecting
the contributions of the other mechanosensitive channels found in
wild type cells. Based on this model, with our typical mean
numbers, osmotic protection can be extended to shocks of
,500 mOsm, in reasonable agreement with the observed hypo-
osmotic challenge assays . Interestingly, in experiments
comparing the survival rates of the wild type strain MG1655
(,300 MscL channels) and the mutant strain MLG910-DrpoS (10–
20 MscL channels), we observe no significant difference in survival
rates for shocks up to 500 mOsm (Figure S5), similar to previous
results . However, a more complete analysis requires
consideration of the other mechanosensitive channels.
Since MscL has the highest gating tension (neglecting the effects
discussed in previous section), the other channels will likely be
activated before MscL in a hierarchical fashion, according to their
respective gating tensions. Also, it is known that the presence of
MscK or MscS, by themselves at physiological expression levels, is
sufficient to provide some protection or even complete rescue from
downshock , respectively. The relative number of MscS
channels has been reported to be 2–5 times greater than the
number of MscL channels, evenfor rpoS deletion strains . In this
context, it is likely we are overestimating the impact of MscL levels
on osmotic rescue for wild-type like strains. In order to include these
effects, we need to know the water conductance and the absolute
numbers of each of the other channels. At this time, these data are
less certain than the data for MscL. This motivates the need for
future censuses for the other mechanosensitive channels.
The techniques demonstrated in our current work may provide
another means of addressing the connection between survivability
and channel expression level. For example, we could image our
calibrated fluorescent strains during osmotic shock and throughout
the recovery process. In principle, it should be possible to
determine how much enhanced MscL levels in wild-type and
various channel deletion strains affect survivability with single-cell
resolution. If it is true that more channels leads to higher survival
rates, it is interesting to speculate on how the variability of the cell-
to-cell MscL distributions (as measured by the Fano factor)
increases substantially with stress, age and salt (Figs. 4B and 4C). It
is possible that the increased variability is a population survival
strategy. The majority of cells would not be required to prepare for
a worst-case possible osmotic catastrophe. A population of cells
can ‘‘hedge its bets’’ on a small percentage of cells in the highest
expressing region of the distribution. If survival rates turn out to be
weakly dependent on the number of channels, it begs the question
of why is there an apparent excess of channels and why is there
upregulation of these channels under stress conditions?
Materials and Methods
A construct that coded for a MscL-sfGFP fusion protein (see
Figure S6 and Fusion Protein Design and Sequence in Supporting
Figure 5. The dependence of critical tension needed to open
one channel on the total number of channels. Estimates of Eopen-
Eclosedshow considerable variation due to experimental uncertainties
and the effect of lipid composition . For illustration, we chose
representative values found in the literature that reflect the range of
values: 10.0 kBT (red solid line) , 18.6 kBT (green solid line) , and
51.0 kBT (blue solid line) . Dashed lines show t1/2the tension, where
Popen=0.5. The area change DA was taken to be 10 nm2.
Single-Cell Census of Mechanosensitive Channels
PLoS ONE | www.plosone.org9March 2012 | Volume 7 | Issue 3 | e33077
Information S1 for details) was chromosomally integrated in to the
MG1655 strain by recombineering with lambda Red-mediated
homologous recombination . We chose a negative selection
scheme to avoid introducing an antibiotic resistance marker in the
fusion construct (see Figure S7 and Chromosomal Integration Strategy in
Supporting Information S1 for details). To verify successful
integration, multiple colonies were picked for single colony PCR
amplification of the MscL region. The mass of the desired
fragment was confirmed by agarose gel electrophoresis. The PCR
fragments were purified and sent for DNA sequencing (Laragen)
for final verification.
Growth Conditions and Cell Preparation
Starter cultures were grown aerobically in 5 mL of LB-Miller
media  in the presence of appropriate antibiotic (except
MG1655 strain) at 37uC overnight. The following morning, LB-
Miller or M9 minimal media (without supplements) was inoculated
at 1:1000. The carbon source in minimal media was 0.5% glucose
or 0.5% glycerol. Samples for Western blots (,900 mL) were
grown in 2L flasks to the desired OD600. The volume of the culture
was measured and cells were pelleted by centrifugation (Beckman-
Coulter Avanti J-20, 6000 rpm for 15 min at 4uC). Pellets were
frozen overnight (220uC) and resuspended in 50% glycerol to a
volume of 10 mL. Samples for microscopy were grown as
described earlier in 50 mL of desired media. Five 1 mL aliquots
at different values of OD600were used to prepare the sample used
for fluorescent microscopy data collection.
Each cell resuspension (for Western blots) was diluted in
TBS+SDS buffer (20 mM Tris, 150 mM NaCl, 1% SDS wt/wt) to
a concentration equivalent to cell culture of an OD600of ,10.
45 ml of this mixture was taken and mixed ,10 times with a
serological pipette, until a large change in turbidity was observed.
350 mL of PMSF (phenylmethylsulfonyl fluoride) protease inhib-
itor (Sigma P7626) were added to each lysate, followed by
additional pipette mixing. Next, each sample was homogenized
using a blade-based homogenizer for 15–30 s to shred the
remaining DNA and insoluble fraction. At this level of
preparation, samples could be run on gels. However, upon
ultracentrifugation (50,000 g), these samples typically still pro-
duced a pellet, indicating the presence of murein sacculi or
possibly even unlysed cells. More importantly, when these lysates
were run on a gel, on occasion, we observed poor band formation,
streaking or clogging of lanes. To ensure complete lysis and
consistency of successive gel runs, the samples were clarified by
passing them 5 times through a microfluidizer (Microfluidics M-
110L) operating at 4uC and ,18000psi. Approximately 10 to
15 mL of the undiluted fraction was collected for Western blot
analysis. These samples produced no measurable pellet after
ultracentrifugation and ran consistently on gels over multiple
repetitions. The addition of the homogenizer and microfluidizer
steps led to a marginal gain, typically 5%–10%, in the measured
number of detected MscL channels. Any error due to concentra-
tion changes or proteolysis introduced by these additional stages
was estimated by a mock lysis procedure see Figure S8 and Protein
Loss During Lysate Preparation in Supporting Information S1 for
details) and is reflected in the error bars for the Western blot
SDS-PAGE was performed with fixed percentage crosslinked
gels (NuPAGE Novex 8% Bis-Tris, Invitrogen WG1002BX10) to
ensure even transfer of the proteins across the entire running
length of the gel. In each lane, we loaded a predetermined volume
of each corresponding lysate, mixed with NuPAGE LDS Sample
buffer (Invitrogen NP0007). The volume of lysate was adjusted to
provide a load of ,20 mg of total mass of cells (,20 ml of lysate at
OD600,10) for each lane. We empirically determined that this is
the maximum total mass of cells that can be loaded per lane which
still leads to consistent blotting results. As a negative control, we
used the lysate from the MJF612 strain. Serial dilutions of purified
protein (generous gift from Troy Walton) were run alongside with
the lysate and were used for calibration. Loaded gels were run in
MES buffer (Invitrogen NP0002) at 200 V for 35 minutes. The
proteins were transferred using Nitrocellulose iBlot Gel Transfer
Stacks (Invitrogen IB3010-01) and blocked in TBS 5% milk 2%
BSA buffer (20 mM Tris, 150 mM NaCl, pH 7.5) for 1 hour at
room temperature. The primary antibody recognizing the
appropriate epitope – MscL (gift from S. Sukharev), GFP (Roche
Applied Science 11814460001) or RpoS (Santa Cruz Biotechnol-
ogy sc-101602) - was added to the blocking buffer at a dilution of
1:5000 for overnight incubation at 4uC. The next day, membranes
were washed twice with TBS 5% milk 2% BSA buffer and
incubated 1 hour at room temperature in the appropriate HRP-
conjugated secondary antibody - anti-rabbit (GE Healthcare
NA934VS) or anti-mouse (GE Healthcare NA931VS). After
incubation, the membranes were subjected to three successive
5 minute washes in TBS buffer and developed for 5 minutes
in SuperSignal West Femto Maximum Sensitivity Substrate
(Thermo Scientific 34095). Developed membranes were imaged
with a home-made gel imager that used an EMCCD chip
camera (Andor DU-897E). Typical exposure times were 100 ms
to 1 s.
Over the course of a few Western blots, the reference protein
concentrations were empirically adjusted to encompass the range
of chemiluminescence shown from the bands of interest. For each
quantitative Western blot, we measured the intensities of the
reference bands and the lysate bands (Figure S9A, first row) and
normalized them to the dimmest band. From the reference band
intensities and knowledge of how many channels we loaded into
the references (Figure S9A, second row), we established a linearly-
fit, calibration curve of relative intensity vs. number of channels
(Figure S9B). From the calibration curve, we extrapolated the total
number of channels present in each lysate band based on its
intensity (Figure 9A, third row). We found the equivalent number
of cells loaded in each lane (Figure S9A, fourth row) by calibrating
the cell density of the original cell culture using disposable
hemocytometers (see Table S3 and Calibrating the Cell Density for
OD600Measurements in Supporting Information S1). Typically, the
actual equivalent number of cells loaded in each lane ranged from
0.46108to 36108. From these data, we determined the number of
channels per cell (Figure S9A, fifth row).
The anti-MscL blots showed multiple bands for a given lane
(Figure 1A), presumably related to the polyclonal nature of the
antibody. We identified the legitimate MscL bands (15 kDa) by
observing which of the bands from the reference protein
concentrations (Figure 1A, lanes 1 through 5) demonstrated an
intensity trend that matched the concentration trend of the
reference proteins (progressively increasing by a factor of two). For
the lanes containing cell lysates, we identified the MscL bands by
matching their running positions on the blot to the reference MscL
bands (15 kDa marker on Figure 1A), allowing us to discriminate
against the non-specific bands (25 kDa, 40 kDa, ,75 kDa). The
control MJF612 lysate, which has MscL deleted, establishes there
is no detectable non-specific band in the mass range near 15 kDa.
For the anti-GFP blots, we note that, within our detection limit
(5,10 molecules/cell), there are no bands corresponding to free
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PLoS ONE | www.plosone.org 10 March 2012 | Volume 7 | Issue 3 | e33077
sfGFP (,23 kDa), indicating the vast majority of sfGFP molecules
are attached to MscL.
Single Cell Fluorescence Microscopy
A ,3 mL sample of the culture was placed between two RCA-
SC2 cleaned  low-autofluorescence glass (Corning D-263)
cover slips. The edges of the slips were sealed with VALAP,
forming a 22 mm622 mm62 mm viewing chamber. The cells were
imaged in laser-excited (473 nm) epi-fluorescence mode at 1006
magnification (Olympus NA 1.45 TIRFM objective) using a
homemade inverted TIRF/epi-fluorescence microscope. The
images were recorded on an electron multiplying CCD camera
(Andor iXon+ DU-897E). For each sample, over 250 fields of view
were acquired. Fluorescent microscopy images were analyzed
using a customized MATLAB program based on the SCHNITZ-
CELL segmentation program (a generous gift from M. Elowitz’s
lab). Images were median filtered to reduce spurious pixel noise.
Next, a threshold mask was created for every frame by hand
setting a threshold value for each sample (200 for MLG910-DrpoS
strain, 100 for autofluorescence measurement and 500 for the rest
of the cells). These masks were used to segment out individual cells
from the original images and the total fluorescence of each
segmented cell could be recorded. A last stage of manual selection
was made on the segmented cells, where the selection criteria were
based on morphology. Typically, we retained 800 to 3000 cells for
each condition. Histograms were created from the selected cells for
Single Molecule Fluorescence Calibration
We calibrated the number of fluorescent counts associated with
a single sfGFP protein by measuring the average size of single-step
photobleaching events . A reference sample of purified MscL-
sfGFP protein (,10 pM) was loaded into a viewing chamber as
described above. In order to maximize signal-to-noise, the
fluorescent samples were excited with laser-based TIRF illumina-
tion. Movies of the photobleaching molecules were recorded at 4
frames per second. Individual molecules were segmented with a
modified version of the MATLAB based PolyParticle-Tracker
program . Typical single-molecule time traces are shown in
Figures S10A through S10C. The traces were manually selected
and fit to step functions. A histogram of counts was constructed
and a mean signal was calculated (Figure S10D). The mean value
was multiplied by a TIRF/epi-fluorescence calibration factor
(described below). The number of MscL subunits per cell was
obtained by dividing the total fluorescence signal from a given cell
by mean fluorescence counts from a single sfGFP molecule. To
determine the number of channels, we assumed there were five
subunits per channel.
In order to use a signal from single molecules recorded in TIRF
to calibrate the signal from single cell recorded in epi-fluorescence,
we collected additional set of data used to calculate what we call
TIRF/epi-fluorescence calibration factor. A solution of 40 nm
yellow-green fluorescent microspheres (Invitrogen F8771) was
prepared for imaging as described earlier. The images of 50 fields
of view were saved in both TIRF and epi-fluorescence. The
PolyParticle-Tracker program was used to find a TIRF/epi-
fluorescence ratio for single beads.
strains. (A) Images of plates comparing cell survival rates after
Osmotic shock assay results for various
a 0.5 M NaCl osmotic downshift for MG1655, MJF612 and
MJF612 expressing MscL-sfGFP (MJF612+mscL-sfGFP). Rows
represent serial dilutions, where the dilution factors are shown to
the left of the rows of the first panel. The dilutions factors are
relative to the previous row. Columns represent repetitions of the
same sample. (B) Mean survival rate determined from the last plate
row for the various strains for a given osmotic shock. The results
are normalized to colony forming units from the MG1655 strain.
The errors bars are the standard deviation of 5 trials.
single cell. (A) Before photo-bleaching (0 s). (B) Photo-bleaching
(0.7 s) (C) Recovery of the signal (8.4 s). The slow recovery of
fluorescence is consistent with diffusion rates typical of fluorescent
proteins mobile in the cell membrane, as opposed to the sub-
second recovery times which are characteristic of free proteins
expressed in the cytoplasm.
Confocal images demonstrating FRAP for
same antibody. Arrows indicate the protein of interest. Other
bands are the result of non-specific binding. Lysate from MJF612
strain (612, lane 6) was used as a negative control. The cells used
for lysate preparations were cultured to exponential (exp) and
stationary phase (stat) in LB-Miller (LB), M9+glucose (U), and
M9+ glycerol (Y). For the reference lanes (1–5), the numbers near
the reference bands are the number of picomoles loaded. For the
lysate lanes (7–18), the numbers near the lysate bands are the
number of picomoles determined by extrapolation from the
reference band intensities. (A) Blot performed with MscL antibody.
Lanes 1–5 are reference loads of purified MscL protein. Lanes 7–9
and 13–15 are MscL-sfGFP levels in MLG910 (MLG). Lanes 10–
12 and 16–18 are MscL levels in MG1655 (WT). (B) Blot
performed with GFP antibody. Lanes 1–5 are reference loads of
purified MscL-sfGFP proteins. Lanes 7–9 and 13–15 are MscL-
sfGFP levels in MLG910 (MLG). Lanes 10–12 and 16–18 are
samples from MG1655 expressing WT MscL and are additional
negative controls for the GFP antibody. Comparison of lanes 7–9
and 13–15 from both blots demonstrate the equivalency of the two
Detection of MscL and MscL-sfGFP with the
function of OD in MLG910-DrpoS strain. For M9+glycer-
ol+500 mM NaCl, we observed a doubling of the mean number of
channels. The errors bars reflect the uncertainties in the absolute
Mean number of MscL-sfGFP channels as a
subjected to a 0.5 M NaCl osmotic shock. (A) Images of
plating results after hypo-osmotic challenge. Rows represent serial
dilutions, where the dilution factors are shown to the left of the
rows of the first panel. The dilutions factors are relative to the
previous row. Columns represent repetitions of the same sample.
(B) Mean probability of survival determined from the number of
colony forming units after an overnight incubation. The results are
normalized to colony forming units from the control plate (no
shock). Errors bars are the standard deviation of five trials.
MG1655 (WT) and MLG910-DrpoS strains
letter amino acid sequence for MscL, the linker, and sfGFP are
colored in brown, pink, and (fluorescent) green, respectively.
Fusion protein design and sequence. The single
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PLoS ONE | www.plosone.org 11 March 2012 | Volume 7 | Issue 3 | e33077
Forward Primer and 23.01R Reverse Primer used for integration.
(B) Auxiliary plasmid pZS4*-em7-galK. 4* denotes spectinomycin
resistance gene, em7 is a synthetic prokaryotic promoter, and galK
is the galactokinase coding gene. (C) Native MscL coding region in
E. coli. (D) 4*-em7-galK cassette inserted into MscL coding region.
(E) MscL-sfGFP fusion inserted into MscL coding region. The
gene is under control of the native MscL promoter.
Chromosomal integration strategy. (A) 23.01
Western blots were performed with MscL antibodies. The aliquots
from different stages of mock lysate preparation (purified MscL
protein of known concentration added to a MJF612 culture) were
run in duplicate alongside with the reference protein loads
(References). The number above reference each band is the
number of picomoles loaded. The aliquots (right to left) were taken
after adding lysis buffer to pelleted MJF612 cells (AL), after using a
homogenizer (AH), and after passing the sample through a
microfluidizer (AF). The numbers above the lysate bands show the
number of picomoles measured based on extrapolation from the
reference band intensities. Ideally, the mock lysate bands (lanes 4
through 6) should have the same intensity as the 0.675 picomole
reference band (lane 3). The other bands are results of non-specific
Protein loss during lysate preparation.
blots. (A) Representative bands for MG1655 (WT) with a
summary table of measured and calculated numbers. (B) Linear fit
to reference band intensities used to determine the number of
channels for each lysate. Only the linear range of detection is used
for this fit (lanes 2 through 5). All of the lysate band intensities
(Figure S9A row 1, lanes 7 through 12) occur within this range.
The last data point, demonstrating saturation effects from lane 1,
has been excluded from the fit.
Absolute calibration of quantitative Western
molecule traces and histogram of counts. (A) A trace with
Single molecule calibration: typical single
one photobleaching step. (B) A region of the trace with two
photobleaching steps. The data points not used for fitting are
marked in blue. (C) A typical single molecule trace that was
rejected. (D) Histogram of counts.
Supporting Information S1
lated to Materials and Methods.
Supporting information re-
Osmolalities of the media used to culture the
gamma distribution fitting.
A summary of results for channels counts and
ments for various growth conditions.
Cell density calibration of OD600 measure-
We would like to thank Doug Rees, Ian R. Booth, KC Huang, Liz Haswell,
Rob Brewster, Troy Walton, Hernan Garcia, Paul Wiggins, Zhenfeng Liu,
Tristan Ursell, and Kira Veley for many helpful comments and discussions;
the physiology course and its attendees at the Marine Biology Laboratory
in Woods Hole, MA for providing the equipment and overall intellectual
environment that was the inspiration for this work; Akiko Rasmussen for
performing valuable electrophysiology measurements; and Samantha
Miller, Susan Black, Troy Walton, Hernan Garcia, and the CGSC at
Yale University for materials and technical expertise.
Conceived and designed the experiments: MBF HJL HAD CSG RP.
Performed the experiments: MBF HJL HAD . Analyzed the data: MBF
HJL HAD . Contributed reagents/materials/analysis tools: MBF HJL
HAD CSG RP. Wrote the paper: MBF HJL HAD CSG RP.
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