Single molecule methods with applications in living cells

COBIOT-1193; NO. OF PAGES 8

Single molecule methods with applications in living cellsFredrik Persson, Irmeli Barkefors and Johan Elf

Available online at www.sciencedirect.com

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

IntroductionThere are two main reasons for the use of single mol-

ecule 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-localiz-

ation have therefore proven useful as in vivo comp-

lements 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].

Please cite this article in press as: Persson F, et al.: Single molecule methods with applications i

www.sciencedirect.com

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 microscopyThe most common principle for single molecule detec-

tion 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 diffrac-

tion limited fluorescence microscopy experiment

becomes inherently single molecule [4�]. For more abun-

dant proteins there are methods, for example, photo-

activation, to ensure that only a fraction of the molecules

are fluorescent at any given time [5,6��].

LabelingThere are two major classes of fluorescent labels: syn-

thetic dyes [7] and fluorescent proteins (FPs) [8]. Syn-

thetic dyes have the benefit of superior photo-physical

properties and are more robust than FPs; however, label-

ing molecules inside living cells generally introduces

some non-negligible issues, for example, cell wall per-

meability, target specificity, and labeling stoichiometry.

These issues often result in insufficient labeling or exces-

sive 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.

n living cells, Curr Opin Biotechnol (2013), http://dx.doi.org/10.1016/j.copbio.2013.03.013

Current Opinion in Biotechnology 2013, 24:1–8


[email protected]


http://www.sciencedirect.com/science/journal/09581669

2 Systems biology


Furthermore, FP-labeling will often interfere with

protein functionality and can also cause protein aggre-

gation [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 imposs-

ible 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 backgroundOne 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 auto-

fluorescence [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 exci-

tation 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 glass-

sample interface. Since the evanescent field decays expo-

nentially, only molecules that are very close to the inter-

face (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

Please cite this article in press as: Persson F, et al.: Single molecule methods with applications in


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.

LocalizationWhen 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 point-

spread 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, decreas-

ing 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 Caulobactercrescentus [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 rela-

tively slow to operate. However, by introducing astigma-

tism in the optical system [31] or by using multiple focal

planes [32] it is possible to obtain 3D localization infor-

mation 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 gener-

ally more complicated to implement.

Application: single molecule experiments forlow copy number experimentsMany central biological processes involve molecules that

are present in very low copy-numbers per cell. Relevant invivo investigation of these processes requires single mol-

ecule 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 poly-

merase exchange during bacterial DNA replication

(Figure 2a) and Hammar et al. [4�] demonstrated the

mechanisms by which transcription factors find and bind

living cells, Curr Opin Biotechnol (2013), http://dx.doi.org/10.1016/j.copbio.2013.03.013



Single molecule methods in vivo Persson, Barkefors and Elf 3


Figure 1

Detector

Laser I

Lase

r II

Sample

EXPERIMENTALSET-UP

SINGLE PARTICLE TRACKING

0 ms

3 ms

6 ms

9 ms

12 ms

LOCALIZATION

PointSpreadFunction

State 2

State 3

State 1

D2

D1k1,3

k2,1 k2,3

D3

C. A

NA

LYS

IS &

CLA

SS

IFIC

ATIO

N

3 State Model

Fast shuttersDM1

DM2

(a)

(b)

100x N.A. 1.42

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



Application: single molecule experiments tostudy kinetics in asynchronous moleculesThe 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 mol-

ecules through distinct binding and dissociation events




4 Systems biology


Figure 2

Repressed (-IPTG) Induced (+IPTG)

Osym

LacI DNA

Osym

LacI-IPTG DNA

lacI-venusOsym

1.0

0.8

0.6

0.4

0.2

frac

tiona

l bin

ding

250200150100500

time [s]

LacI-Venus

auto-repression

(a) (b)

(c) (d)

3x104

2x104

Flu

ores

cenc

e (a

.u.) equivalent Y

P et1x104

0

3

2

1

0

0 2 4 6 8 10 12 14 16 18 20Time (s)


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 diffu-

sion. 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 exper-

iment [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 ran-

ging 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



the mobile molecules at different time scales and deter-

mine how short exposure is required to freeze the mol-

ecules 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






Figure 3

(a)

0

0.4

0.8

1.2

1.6

0

0.4

0.5

0.6

0.7Shp2SH2(C)

Jak2SH2

Shp2SH2(N)

Grb2SH2

Src2SH2

0.1

0.2

0.3

0 1 2 3 4 5membrane

membrane

Fast

Fastp-Tyr

SH2 domain

(II) Dissociationwith rebinding

(I) Simple dissociation

Slow

dwell-time >> 1/koff

dwell-time = 1/koff

Fast Rebind

Escape

membrane0 0.4 0.8 1.2

Δt (sec) 1/<λ>, Dwell-time (sec)D

eff (

10-8

cm

2 /sec

)

MS

D (

µm

2 )

(b)

0.031

0.026

D1 = 0.24 µm2/s[Δt-1 ] [Δt-1 ]

0.03

5

0.04

3

0.027

0.051

0.003

0.002

Hfq with rifampicin treatmentHfq without rifampicin treatment

τ1 = 27 Δt

D2 = 0.75 µm2/sτ2 = 14 Δt

D3 = 2.6 µm2/sτ3 = 19 Δt

D1 = 0.71 µm2/sτ1 = 32 Δt

D2 = 3.1 µm2/sτ2 = 38 Δt

Hfq

DNA

RNA-Pol

Ribosome

Protein

sRNA

mRNA

mRNA


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 dataThe 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 disap-

pearance 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.



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 distri-

bution of step lengths on a fixed time scale. Both methods

can be used to identify parameters in presumed under-

lying models, or even to discard too simple models. The

problem with both methods is that introduction of an




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 stat-

istics (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 prioriknowledge 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��].

ConclusionsIt 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 correspond-

ing 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 open-

source 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 bio-

logical 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.



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http://dx.doi.org/10.1038/nmeth.2367

http://dx.doi.org/10.1038/nmeth.2367


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http://dx.doi.org/10.1098/rstb.2012.0025

http://dx.doi.org/10.1529/biophysj.108.128751

http://dx.doi.org/10.1529/biophysj.108.128751


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Single molecule methods with applications in living cells