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Available online at www.sciencedirect.com
Single molecule methods with applications in living cells
Fredrik Persson, Irmeli Barkefors and Johan Elf
Our knowledge about dynamic processes in biological cells
systems has been obtained roughly on two levels of detail;
molecular level experiments with purified components in test
tubes and system wide experiments with indirect readouts in
living cells. However, with the development of single molecule
methods for application in living cells, this partition has started
to dissolve. It is now possible to perform detailed biophysical
experiments at high temporal resolution and to directly observe
processes at the level of molecules in living cells. In this review
we present single molecule methods that can easily be
implemented by readers interested to venture into this exciting
and expanding field. We also review some recent studies where
single molecule methods have been used successfully to
answer biological questions as well as some of the most
common pitfalls associated with these methods.
Addresses
Department of Cell- and Molecular Biology, Science for Life Laboratory,
Uppsala University, Sweden
Corresponding author: Elf, Johan ([email protected])
Current Opinion in Biotechnology 2013, 24:xx–yy
This review comes from a themed issue on Systems biology
Edited by Orkun S Soyer and Peter S Swain
0958-1669/$ – see front matter, Published by Elsevier Ltd.
http://dx.doi.org/10.1016/j.copbio.2013.03.013
Introduction
There are two main reasons for the use of single molecule techniques in living cells. First, it enables studies
of intracellular processes that involve scarce molecules
in individual cells. Second, it makes it possible to gather
information about molecular kinetics that traditionally
only could be studied in vitro using biochemical assays
with purified components allowing for rapid mixing and
quenching. In vivo, such synchronized perturbations
from the equilibrium are usually not possible, creating
a need for single molecule techniques in the study of
intermolecular binding and dissociation reactions in the
living cell. Straightforward single molecule techniques
based on changes in diffusion properties or co-localization have therefore proven useful as in vivo complements to traditional biochemical techniques for
studying intermolecular interactions. Using more
advanced techniques, based on, for example, single
molecule FRET, it is also possible to gain access to
detailed information about intramolecular states [3].
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However, even simple single molecule studies in living
cells do present specific challenges and a successful
experiment relies on bright and specific labels as well
as low fluorescence background under reproducible
experimental conditions in immobilized healthy cells.
We will briefly review some of the recent attempts to
overcome these problems.
Single molecule fluorescence microscopy
The most common principle for single molecule detection is regular wide field fluorescence microscopy. The
requirements on the system, as compared to standard
fluorescence microscopy, are dictated by the low number
of photons emitted from a single molecule. The most
crucial parts of the set-up are therefore: a highly photon
sensitive camera (usually based on EMCCD technology),
a high numerical aperture objective, high quality filters,
and a stabile light source [1,2].
The single molecule epithet essentially comprises that
only a few molecules are fluorescent (or rather detected)
simultaneously. Many macromolecules, for example,
some transcription factors, are so dilute that any diffraction limited fluorescence microscopy experiment
becomes inherently single molecule [4]. For more abundant proteins there are methods, for example, photoactivation, to ensure that only a fraction of the molecules
are fluorescent at any given time [5,6].
Labeling
There are two major classes of fluorescent labels: synthetic dyes [7] and fluorescent proteins (FPs) [8]. Synthetic dyes have the benefit of superior photo-physical
properties and are more robust than FPs; however, labeling molecules inside living cells generally introduces
some non-negligible issues, for example, cell wall permeability, target specificity, and labeling stoichiometry.
These issues often result in insufficient labeling or excessive dye that contributes to background noise and cross
reactivity.
Considering these challenges it is not hard to understand
why synthetic dyes have been used mainly to study
membrane proteins in living cells. However, recently
developed methods based on fusion protein tags [9,10]
show increased usability for live-cell imaging [11,12].
In contrast, genetically encoded FPs naturally achieve
perfect stoichiometry as well as target specificity.
However, the use of FPs introduces the potential
problem of maturation, which determines how fast
the fluorophore can be detected after expression.
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2 Systems biology
Furthermore, FP-labeling will often interfere with
protein functionality and can also cause protein aggregation [13,14].
Proteins are the most commonly tagged biomolecules;
however, using hybridization probes [15] it is also possible
to tag for example single RNAs in vivo. Alternatively, a
two-step labeling method can be used which is based on
an introduced loop structure in the RNA, potentiating
binding to a fluorescently tagged MS2 coat protein [16].
If the target of interest is abundant such that it is impossible to separate the molecules if they are simultaneously
excited, there is a need for fluorophores that can be
switched on and off, or that can be converted between
different fluorescent states (e.g. red and green). These
fluorophores are often referred to as photo-switchable,
photo-activatable or photo-convertible depending on
their detailed mechanism and exist in a multitude of
variants, often as derivatives of well-known FPs [5,8].
The use of photo-convertible dyes requires that an
additional light source can be introduced in the light
path in the optical set-up (Figure 1a).
Suppressing the auto fluorescent background
One of the major challenges of fluorescent microscopy in
the living cell is the high background caused by cellular
auto-fluorescence and fluorescent species in the culture
medium, for example, Riboflavin. This is also one of the
major reasons why many pioneering studies have been
performed in bacteria under conditions with low autofluorescence [17,18]. Since cellular auto-fluorescence is
usually largest in the green part of the spectrum, it is wise
to favor red fluorophores if other desired properties, for
example, maturation rate, are sufficient [19]. Another
efficient way of reducing background is to selectively
excite the fluorophores in a well-defined plane. This can
be implemented either by side-ways illumination with a
focused beam (SPIM), or by slightly shifting the excitation angle in a normal microscope to cause total (or near
total) internal reflection (TIRF). Recent advances in
SPIM enables excitation of very thin planes, but this
usually requires non-standard optical set-ups [20]. As it is
easy to implement, TIRF is by far the most widely used
technique to minimize background fluorescence. As the
name implies the light used for TIRF imaging never
penetrates into the sample; instead the fluorophores are
excited by an evanescent field that forms at the glasssample interface. Since the evanescent field decays exponentially, only molecules that are very close to the interface (within 100–300 nm) will be detected, making TIRF
optimal for imaging of membrane proteins. However,
conclusions regarding structures or processes in other
parts of the cell should be made with caution.
In a variation of TIRF, entitled highly inclined and
laminated optical sheet (HILO) microscopy, a thin sheet
Current Opinion in Biotechnology 2013, 24:1–8
of excitation light penetrates the sample at an angle,
making the method in a way analogous to SPIM [21].
HILO thus has the benefit of being able to detect
fluorophores inside the cell.
Localization
When the target molecule has been adequately labeled
we need ways to identify the single fluorophore and to
localize it with high accuracy (20 nm). Since the accuracy
by which a single photon is transmitted through the
optical system is limited by diffraction to l/
2 250 nm, the average localization of several photons
(N) is typically used to estimate the location of the point
source to accuracy l/2HN [22]. This is often achieved
by fitting the detected fluorescent signal to a model pointspread function (PSF), usually a Gaussian (Figure 1c).
Other approaches, such as wavelet analysis [23], stable
wave detection [24] and radial symmetry [25], have also
proven very powerful and recent advances have been
made in separating adjacent fluorescent objects, decreasing the limitation to very sparse fluorescent emitters [26–
29]. Addition of a second fluorophore makes it possible to
compare the localization of different targets and to find
colocalization. This approach was employed by Ptasin
et al. to show that ParB-stimulated ParA depolymerization
contributes to chromosome segregation in Caulobacter
crescentus [30].
Localization is not limited to planes but can easily be
expanded to three spatial dimensions (3D). Traditionally
3D images have been obtained with scanning confocal, or
two-photon, microscopes, which are expensive and relatively slow to operate. However, by introducing astigmatism in the optical system [31] or by using multiple focal
planes [32] it is possible to obtain 3D localization information with a regular fluorescent microscope. Similar to
confocal microscopy, the performance is decreased in the
third dimension, usually by a factor 1.5–2. More advanced
methods with higher 3D accuracy are available, including
4Pi microscopy [33], interferometric microscopy [34] and
double helix PSF microscopy [35,36], but they are generally more complicated to implement.
Application: single molecule experiments for
low copy number experiments
Many central biological processes involve molecules that
are present in very low copy-numbers per cell. Relevant in
vivo investigation of these processes requires single molecule sensitivity since overexpression of labeled targets
would alter the process of interest, for example, by
saturating relevant binding sites. Furthermore, when
monitoring individual components in these processes
their single molecule nature can be directly assessed.
In this way, Lia et al. [37] successfully monitored polymerase exchange during bacterial DNA replication
(Figure 2a) and Hammar et al. [4] demonstrated the
mechanisms by which transcription factors find and bind
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Single molecule methods in vivo Persson, Barkefors and Elf 3
Figure 1
Sample
(a) EXPERIMENTAL
SET-UP
3 State Model
D2
State 2
k2,1
k2,3
State 1
Laser I
DM2
DM1
Fast shutters
Detector
(b)
D1
D3
k1,3
State 3
C. ANALYSIS & CLASSIFICATION
Laser II
x N.A. 1.42
100
SINGLE PARTICLE TRACKING
0 ms
LOCALIZATION
3 ms
Point
Spread
Function
6 ms
9 ms
12 ms
Current Opinion in Biotechnology
Setup and flow of single molecule fluorescence localization and tracking in vivo. (a) A schematic setup for single molecule localization and tracking
experiments [5]. The light from an imaging (excitation) laser (Laser I) and an optional photo-activation laser (Laser II), commonly at 405 nm wavelength, is
combined using a dichroic mirror (DM1). The light is then reflected to the objective using a second dichroic mirror (DM2) to activate and excite the
fluorophores in the sample. The resulting fluorescence is collected and passes through DM2 to the detector, commonly an EMCCD camera. (b) Single
particle tracking. The local area around each individual fluorescence signal is fitted with a 2D Gaussian giving a subpixel estimate of the molecule position
and the localization accuracy [21]. Other approaches such as, for example, wavelets or radial symmetry can also be used [22,24]. Single molecule
trajectories are created by linking positions in adjacent image frames [48,61]. (c) The trajectory data are analyzed based on, for example, distributions of
diffusion constants and fit to theoretical models [46]. In some cases Bayesian interference can also perform the detailed model selection data [45].
individual binding sites in the bacterial chromosome
(Figure 2b). In both these experiments single molecule
detection was used to probe molecular interactions in the
natural low copy number regime and not as a way to get
around the problem that averaging properties over many
molecules in different states of binding hides the relevant
information
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Application: single molecule experiments to
study kinetics in asynchronous molecules
The most important reason for exploring single molecule
techniques in vivo might be the possibility to learn
something about kinetics from an ensemble of molecules
near equilibrium. If you could follow individual molecules through distinct binding and dissociation events
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4 Systems biology
Figure 2
(b)
(a)
3x104
2x104
2
1x104
1
equivalent YP et
Fluorescence (a.u.)
3
0
0
0
2
4
6
10
8
12
14
16
18
20
Time (s)
(d)
Repressed (-IPTG)
Induced (+IPTG)
fractional binding
(c)
1.0
0.8
0.6
lacI-venus
Osym
0.4
LacI-Venus
LacI
LacI-IPTG
DNA
0.2
auto-repression
DNA
Osym
Osym
0
50
100
150
200
250
time [s]
Current Opinion in Biotechnology
Low copy number experiments. (a) By fluorescently tagging DnaQ (a subunit of DNA polymerase III) with YPet and observing the fluorescence intensity
of diffraction limited spots, Lia et al. managed to draw conclusions regarding the polymerase exchange mechanisms in active bacterial replisomes [37].
(b) By monitoring the average time for binding of fluorescently tagged lacI transcription factors to individual operator sites, in conjunction with
alterations of the chromosomal context surrounding the binding site, Hammar et al. could elucidate the mechanism of finding and binding to individual
operator sites [4].
you could estimate the rates for binding and dissociation
from the average times spent in different states of diffusion. Given that you can observe multiple events, you can
even determine the waiting time distribution and learn
more about the underlying processes. One may argue that
the same information can be obtained by a FRAP experiment [38] or FCS [39]. However, since these methods do
not keep track of the identity of individual molecules, the
interpretation will be highly model dependent and it is
hard to disentangle diffusion state occupancies from
diffusion rates.
Biologically relevant dynamics occur on time scales ranging from biomolecular reactions (ms) to the life time of
cells (h). To be able to study freely diffusing molecules
and macroscopic reaction dynamics, a corresponding
temporal resolution is necessary. If one of the reaction
partners is relatively immobile, one approach is to image
Current Opinion in Biotechnology 2013, 24:1–8
the mobile molecules at different time scales and determine how short exposure is required to freeze the molecules in space. The time required will give you an
indication of the duration of interaction with the
immobile partner.
Another way of accessing dynamic information in living
cells is to perform sequential localizations of individual
molecules, that is, single particle tracking (SPT). If the
molecules change state of diffusion upon binding or
dissociation the transition rates between different states
as well as the state life-time distribution can be extracted
from the trajectories. If the labeled species are abundant
it is possible to use photo-activatable fluorophores to
acquire many (100–10 000) independent trajectories from
the same cell [40,62]. Historically, SPT has primarily
been used to study diffusion of membrane proteins
labeled with organic fluorophores, but recent years have
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Single molecule methods in vivo Persson, Barkefors and Elf 5
Figure 3
Shp2SH2(C)
Jak2SH2
Shp2SH2(N)
Grb2SH2
Src2SH2
1.6
MSD (µm2)
1.2
0.8
0.4
0.7
Deff (10-8 cm2 /sec)
(a)
(I) Simple dissociation dwell-time = 1/koff
0.6
p-Tyr
0.5
SH2 domain
membrane
0.4
0.3
(II) Dissociation
with rebinding
0.2
dwell-time >> 1/koff
Escape
0.1
Fast
0
0
0
0.4
0.8
1.2
Fast
0
Δt (sec)
(b)
Fast
1
2
3
4
membrane
membrane
1/<λ>, Dwell-time (sec)
Hfq without rifampicin treatment
Slow
Rebind
5
Hfq with rifampicin treatment
RNA-Pol
Ribosome
DNA
mRNA
D1 = 0.24 µm2/s
τ1 = 27 Δt
35
0.0
0.0
02
03
0.051
D2 = 0.75 µm /s
τ2 = 14 Δt
sRNA
Hfq
0.026
0.027
2
[Δt-1]
0.031
0.0
0.0
43
[Δt-1]
Protein
2
D1 = 0.71 µm2/s
τ1 = 32 Δt
D3 = 2.6 µm /s
τ3 = 19 Δt
D2 = 3.1 µm2/s
τ2 = 38 Δt
mRNA
Current Opinion in Biotechnology
Kinetics in asynchronous molecules. (a) By tracking SH2 modules using TIRF microcopy and photo-convertible dyes, Oh et al. have investigated the
kinetic properties of receptor tyrosine kinase signaling in vivo. To estimate the effective diffusion constants for different SH2 modules, MSD curves
were calculated from single particle traces (Left) and the Deff-values were correlated to the dwell time of the molecules at the plasma membrane
(Middle). Variability in Deff for different modules favors a model with fast rebinding after dissociation (Right) [47]. (b) RNA helper protein Hfq mediates
post-transcriptional gene regulation by facilitating interactions between mRNA and non-coding small RNA. Persson et al. have used photo-convertible
proteins to track single hfq molecules and assign them to different kinetic states based on their diffusive properties. The nature of the different states
(Right) can be deduced by comparing un-treated cell (Left) to cells treated with the transcription blocking drug rifampicilin (Middle) [45].
seen an increase of SPT studies also in the cytoplasm of
living cells (Figure 3) [41,42–44,45,46,47].
How to interpret SPT data
The main challenges of combining single localization
events into trajectories are caused by signal disappearance
due to, for example, blinking, exits from the focal plane,
detection failure or merging and splitting events. These
problems can be reduced by imaging molecules one at the
time and by appropriate choice of fluorophores. For bright
fluorophores, there are several methods available to
recover trajectories suffering from temporal signal disappearance or merging or splitting events (Figure 1b)
[48,49]. However, for many low signal applications it
might be better to adopt a simpler and more restrictive
approach by aborting incomplete trajectories to avoid
misclassification.
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Single molecule tracking data often contains vast amounts
of information including different diffusive states,
possibly representing complex formation or different
modes of diffusion, transition rates between these states,
and spatial localization. The challenge lies in extracting
the information from the highly fragmented data often
obtained from SPT in vivo. Traditionally Mean Squared
Displacement (MSD [47,50,51] and/or Cumulative
Distribution Function (CDF) analysis [52] have been
used to analyze these kind of data.
The MSD describes how far the molecules move on
different time scales and the CDF describes the distribution of step lengths on a fixed time scale. Both methods
can be used to identify parameters in presumed underlying models, or even to discard too simple models. The
problem with both methods is that introduction of an
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6 Systems biology
additional state in the model always leads to a better fit of
the data which makes it difficult to draw conclusions
regarding the number of ‘true’ underlying states, or to
find transitions between states that are overlapping.
These problems can be addressed using Bayesian statistics (BS), which has an inherent ability to handle large
complex and noisy data sets (Figure 1d) [53–55]. While
classical statistics usually calculates the probability of
obtaining the data from a given model, BS infers the
probability of a model given the data, including a priori
knowledge or expectations of the model, if applicable.
The main drawback is that it is quite computationally
demanding.
Several recent studies use BS, for example, to localize
fluorophores [27,28], link trajectories [49], deduce the
mode of transport [51], analyze FRET data [56,57] or to
find underlying states and transitions in SPT data [45].
Conclusions
It should be noted that data from live cell single molecule
experiments are notoriously easy to misinterpret. It is
necessary to develop stringent controls on in vivo activity
of labeled macromolecules and their binding properties
since there are many more potential cross reactions in a
living cell than in the test tube. Things that should be
tested are for example that the labeled molecule can
replace the wild type copy under the relevant conditions,
that the binding is lost when binding sites are removed
and that the labeling procedure and laser illumination do
not alter cell physiology.
In addition, reproducibility is a specific concern. Data
usually have to be collected from several cells to get
sufficient statistics to test quantitative models, and even
if sufficient data can be collected in one cell, several cells
need to be investigated to characterize the cell-to-cell
variability. In order to merge or compare data between
cells, they should be investigated under similar conditions
and sometimes even in the same phase of the cell cycle.
Recent development in microfluidics growth chambers for
live cell single molecule experiments and the corresponding image analysis software [58] will make it feasible to
perform reproducible experiments in the required amount
of cells. Another example of advances in automated
analysis is rapidSTORM, a recently introduced opensource software for localization microscopy [59].
Finally, single molecule experiments in living cells often
need to be complemented by quantitative modeling at a
similar level of detail [60] to determine if the observed
data is expected given geometrical constraints and biological and experimental noise. Quantitative modeling
and simulation of alternative models may also be the only
way to test if these models can be discarded given the
amount and quality of the available data.
Current Opinion in Biotechnology 2013, 24:1–8
References and recommended reading
Papers of particular interest, published within the period of review,
have been highlighted as:
of special interest
of outstanding interest
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Please cite this article in press as: Persson F, et al.: Single molecule methods with applications in living cells, Curr Opin Biotechnol (2013), http://dx.doi.org/10.1016/j.copbio.2013.03.013