Download Imaging ER-to-Golgi transport: towards a

ARTICLE SERIES: Imaging
Commentary
5091
Imaging ER-to-Golgi transport: towards a systems view
Fatima Verissimo and Rainer Pepperkok
European Molecular Biology Laboratory, Cell Biology and Cell Biophysics Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
Authors for correspondence ([email protected]; [email protected])
Journal of Cell Science 126, 5091–5100
ß 2013. Published by The Company of Biologists Ltd
doi: 10.1242/jcs.121061
Journal of Cell Science
Summary
Proteins synthesised at the endoplasmic reticulum (ER) have to undergo a number of consecutive and coordinated steps to reach the
Golgi complex. To understand the dynamic complexity of ER-to-Golgi transport at the structural and molecular level, light microscopy
approaches are fundamental tools that allow in vivo observations of protein dynamics and interactions of fluorescent proteins in living
cells. Imaging protein and organelle dynamics close to the ultra-structural level became possible by combining light microscopy with
electron microscopy analyses or super-resolution light microscopy methods. Besides, increasing evidence suggests that the early
secretory pathway is tightly connected to other cellular processes, such as signal transduction, and quantitative information at the
systems level is fundamental to achieve a comprehensive molecular understanding of these connections. High-throughput microscopy in
fixed and living cells in combination with systematic perturbation of gene expression by, e.g. RNA interference, will open new avenues
to gain such an understanding of the early secretory pathway at the systems level. In this Commentary, we first outline examples that
revealed the dynamic organisation of ER-to-Golgi transport in living cells. Next, we discuss the use of advanced imaging methods in
studying ER-to-Golgi transport and, finally, delineate the efforts in understanding ER-to-Golgi transport at the systems level.
Key words: Early secretory pathway, Endoplasmic reticulum, Golgi, Transport carriers, Microscopy
Introduction
The secretory pathway consists of a number of membrane-bound
compartments, such as the endoplasmic reticulum (ER), the
Golgi complex, and pleiomorphic membrane carriers that
transport proteins and lipids to their destination (Murshid and
Presley, 2004). Remarkably, approximately one-third of all
cellular proteins move through the secretory pathway to reach
their final destination in the intra- or extracellular space
(Dancourt and Barlowe, 2010), underlining the importance of
this pathway for cell function. The current models that describe
how material moves through the secretory pathway are grounded
on fundamental electron microscopy (EM) observations made by
Palade and colleagues (Jamieson and Palade, 1967; Jamieson and
Palade, 1968). Based on this and related work, in 1975, Palade
proposed a model suggesting that the path taken by secreted
proteins occurs in vesicular-like transport carriers that move
vectorially from the rough ER to the Golgi complex and, from
there, to the plasma membrane (Palade, 1975).
Efficient ER-to-Golgi transport requires a number of
coordinated steps (see Fig. 1). In Saccharomyces cerevisiae,
secretory proteins that are synthesised at the ER are sorted and
concentrated by the vesicular coat-protein complex COPII, and
incorporated into COPII-coated transport vesicles that deliver
their cargo to the Golgi complex (Lee et al., 2004; Rossanese
et al., 1999). COPI-coated transport vesicles are then returning
the transport machinery back to the ER (Lee et al., 2004). In
mammalian cells, Drosophila melanogaster and some yeast (e.g.
Pichia pastoris), COPII-coated transport carriers form only at
specialised sites at the ER, the so-called ER-exit sites (ERES)
(Bevis et al., 2002; Herpers and Rabouille, 2004; Stephens, 2003)
(see also Fig. 1). In mammalian cells, COPII vesicles are thought
to form vesicular tubular clusters (VTCs), a more complex
transport intermediate, by homotypic fusion (see Fig. 1 for the
mammalian transport model) (Hughes and Stephens, 2008).
VTCs, subsequently acquire the vesicular coat complex COPI
and then move along microtubules to the Golgi complex where
they deliver their cargo. COPI-coated transport vesicles form at
the Golgi complex to return misfolded proteins and the transport
machinery back to the ER (Fig. 1). Alternative transport models
suggest that COPII vesicles first deliver their cargo in a
microtubule-independent manner to a more stable ER-to-Golgi
intermediate compartment (ERGIC). Secretory cargo is then
thought to move from the ERGIC towards the Golgi complex in
VTC-like structures whose nature is not yet clear (see Fig. 1)
(Appenzeller-Herzog and Hauri, 2006). Although most of the
basic steps in ER-to-Golgi transport are similar in different
species, there are variations regarding transport carriers or
cytoskeleton structures involved, e.g. between plant cells and
mammalian cells, that to date are not completely understood
(Brandizzi and Barlowe, 2013).
The molecular core machinery that is responsible to drive the
different transport steps in the early secretory pathway is
conserved between species, and might be considered as being
largely identified and fairly well characterised (Béthune et al.,
2006; Brandizzi and Barlowe, 2013; Dancourt and Barlowe, 2010;
Gürkan et al., 2006; Hsu and Yang, 2009; Lee et al., 2004;
Lippincott-Schwartz and Liu, 2006; Szul and Sztul, 2011; Zanetti
et al., 2012). However, the additional factors that regulate the
different transport steps in the early secretory pathway in response
to changes in the cellular environment or mediate alterations in the
secretory pathway during the various phases in development or cell
differentiation are still unknown. In vitro biochemical assays were
used very successfully to identify and characterise the core
machinery of the early secretory pathway (Barlowe et al., 1994;
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Golgi complex
TGN
trans
medial
cis
VTCs
COPI
Microtubule
?
*
ERGIC
COPII
ERES
Journal of Cell Science
Ribosome
ER
Key
Sec23
Sec24
Sec13–Sec31
Fig. 1. Illustration of ER-to-Golgi transport in mammalian cells. Shown
are the ER-to-Golgi interface and the transport carriers involved. In mammalian
cells, COPII vesicles bud from ribosome-free areas in the ER, the so called ERexit sites (ERES) (see also Fig. 2A). COPII-coated vesicles vary in size, but are
typically between 60 and 80 nm in diameter. COPII components are directly
involved in cargo selection and membrane bending and, therefore, essential for
protein export from the ER. COPII vesicles undergo homotypic fusion to form
vesicular tubular clusters (VTCs). Although forming VTCs might be partially
coated with COPII and COPI (*) VTCs that move along microtubules in order
to fuse and deliver cargo to the Golgi are COPI-coated. COPI-coated vesicles
also retrieve components of the transport machinery as well as misfolded
proteins from the Golgi and VTCs back to the ER. Typical COPI vesicles are
50–60 nm in size and the size of VTCs varies from 250 nm to 1 mm. There is
some evidence to support the existence of a more stable ER-to-Golgi
intermediate compartment (ERGIC); however, the nature of the carriers that
move cargo from the ERGIC to the Golgi complex it is not clear. TGN, transGolgi network. Arrows indicate the direction of transport carriers; see Table 1
for the roles of minimal COPII and COPI components.
Fries and Rothman, 1980; Lee et al., 2004; Rothman, 1996).
However, these methods have limitations in achieving a full
understanding at the whole-cell or organism level, as this requires
analyses in the context of the whole cell or organism. We propose
that one way to obtain systems-level information is by quantitative
fluorescence microscopy in living cells. Although transport
carriers in the early secretory pathway are typically smaller than
the resolution of conventional light microscopy, recent
technological progress – such as life cell imaging with high
temporal and spatial resolution using fluorescently tagged proteins
(FPs), the development of correlative light and electron
microscopy approaches, as well as the availability of superresolution light microscopy – has taken place. These technologies
and high-throughput microscopy methods, together with the
possibility to perturb gene expression by using RNA interference
(RNAi) in mammalian cells at large scale, have opened new
avenues to gain, indeed, an understanding of the secretory pathway
at the systems level.
Here, we review and discuss distinct imaging approaches to
study the early secretory pathway. We will discuss how they
helped to gain a better understanding of membrane traffic at the
ER-Golgi boundary during the past few years, including the latest
developments in advanced imaging methods that have the
potential to help understanding ER-to-Golgi transport at the
systems level.
Imaging ER-to-Golgi transport in living cells
A major turning point for the field of membrane traffic was the
availability of the green fluorescent protein (GFP) and its spectral
variants (Crivat and Taraska, 2012; Giepmans et al., 2006;
Shaner et al., 2005; Stepanenko et al., 2011). Fluorescent
labelling and time-lapse microscopy provided the means to
visualise almost any protein in its natural environment, and to
monitor its localisation (Huh et al., 2003; O’Rourke et al., 2005;
Simpson et al., 2000) and dynamics in living cells. Most
remarkably, this approach revealed the highly dynamic nature of
the organisation of ER-to-Golgi transport and the organelles
involved (Brandizzi and Barlowe, 2013; Verissimo and
Pepperkok, 2008).
For example, time-lapse microscopy of fluorescently labelled
COPII proteins allowed the visualization of how ERES change
during the cell cycle; they disappear before metaphase and
reappear towards the end of cell division (Stephens, 2003)
(Fig. 2A; supplementary material Movie 1). Imaging of
fluorescently labelled secretory cargo showed that VTCs, which
are highly similar to the ER-to-Golgi intermediate compartment
(ERGIC), are not static structures like the ERGIC (AppenzellerHerzog and Hauri, 2006; Ben-Tekaya et al., 2005), but rather
long-range transport carriers (Presley et al., 1997; Scales et al.,
1997). Moreover, these cargo carriers form in the vicinity of
COPII-labelled ERES and later segregate to acquire the vesicular
coat complex COPI and move towards the Golgi complex in a
microtubule-dependent manner (Shima et al., 1999; Stephens
et al., 2000) (see also Fig. 1; Fig. 2B; supplementary material
Movie 2).
Time-lapse microscopy and fluorescence recovery after
photobleaching (FRAP) (see Box 1) of fluorescently tagged
Golgi markers also revealed the highly dynamic nature of this
organelle (Ward et al., 2001). Moreover, blocking COPIImediated ER-exit by using a dominant-negative mutant of the
COPII component Sar1 causes re-absorption of GFP-tagged
Golgi enzymes to the ER, demonstrating a strong dependence of
Golgi integrity on COPII-mediated ER-exit (Shima et al., 1998;
Storrie et al., 1998; Ward et al., 2001). These results raised the
exciting question whether the Golgi complex is an independent
(static) organelle or is synthesized from ER membranes.
Evidence of the later was obtained recently through monitoring
the biogenesis of a Golgi complex in karyoblasts, in which the
Golgi complex had been initially depleted by laser nanosurgery
(Tängemo et al., 2011).
Multi-colour time-lapse imaging in S. cerevisiae also helped to
shed light on the long-deliberated question of how transport
within the Golgi complex is organised and the nature of its
cisternae is maintained (Losev et al., 2006; Matsuura-Tokita et al.,
2006). In S. cerevisiae, Golgi cisternae are not stacked as in
Imaging ER-to-Golgi
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A
i
ii
iii
Box 1. Different F-techniques
F-techniques are quantitative methods that provide information of
protein dynamics or protein–protein interactions and include
fluorescence microscopy-based methods, such as those listed
below.
0 minutes
iv
585 minutes
v
630 minutes
615 minutes
vi
645 minutes
750 minutes
B
Journal of Cell Science
i
ii
0.3 seconds
iv
iii
1.6 seconds
v
2.1 seconds
1.8 seconds
vi
2.6 seconds
2.9 seconds
Fig. 2. Examples of life cell imaging of ERES and ER-to-Golgi transport.
(A) Life cell imaging of ERES showing their dynamic nature during the cell
cycle. HeLa cells stably transfected with the COPII protein Sec31 labelled
with YFP (Sec31-YFP) were imaged using a spinning disk confocal
microscope; 3D stacks covering 59 different image planes were acquired
every 15 minutes. In interphase, ERES are visible as fluorescent dots
throughout the cell and accumulated in the juxtanuclear area (i). Before
metaphase, the number and intensity of ERES is significantly reduced (ii); in
metaphase they are not visible or their number is further reduced (iii). ERES
then reappear before cell division (iv,v) and are clearly visible in both
daughter cells upon cell division (vi). Scale bar: 10 mm. (B) Double-colour
life cell imaging of the CFP-labelled secretory cargo vesicular stomatitis virus
glycoprotein (VSVG) and the YFP-labelled COPII component Sec24D during
ER-to-Golgi transport. Initially, CFP-VSVG (green) and YFP-Sec24D (red)
colocalise at ERES (i). Subsequently, CFP-VSVG segregates from ERES (ii–
iv) and moves towards the Golgi complex without any apparent YFP-Sec24D
(v); Sec24D remains associated with the ERES (v,vi). In each panel, the side
towards the Golgi is on the right, the arrow indicates the trajectory of CFPVSVG structures, the arrowhead indicates YFP-Sec24D. Scale bar: 2.5 mm.
The images shown in B are reproduced from a movie from Stephens et al.
(Stephens et al., 2000).
mammalian cells but separated from each other (Preuss et al.,
1992); hence, individual cisternea can be visualised and
tracked by time-lapse microscopy. Two studies took advantage
of this feature, describing the labelling of Golgi cisternae with
spectrally distinct FPs (cis-Golgi cisternae with GFP, trans-Golgi
cisternae with RFP), to monitor them in living cells by using
fluorescence microscopy (Losev et al., 2006; Matsuura-Tokita
FRAP
In fluorescence recovery after photobleaching (FRAP), a laser
scanning confocal microscope is used to irreversibly destroy the
fluorophore (e.g. GFP) that is linked to the protein of interest by
photobleaching it with high laser excitation intensity (Axelrod et al.,
1976). Thereafter, the region that has been photo-bleached is
monitored by time-lapse microscopy to quantify the kinetics of
reappearance of the fluorescent signal in the bleached area
(Lippincott-Schwartz et al., 2003; Lippincott-Schwartz and
Patterson, 2003).
FLIP
Fluorescence loss in photobleaching (FLIP) is related to FRAP.
Area(s) within a cell are continuously photo-bleached and the
kinetics of loss of fluorescence outside the bleaching area is
monitored using time-lapse microscopy to determine the kinetics
of exchange of fluorescent material between the bleached and
non-bleached area(s). Using this approach, continuities or material
exchange between organelles, such as the Golgi complex and the
ER, can be revealed (Lippincott-Schwartz et al., 2003; LippincottSchwartz and Patterson, 2003).
iFRAP (inverse FRAP)
This method is also related to FRAP. Here, all the fluorescent
labelling within a cell that is not under investigation is irreversibly
destroyed by photobleaching and the kinetics of the remaining
fluorescence monitored using time-lapse microscopy. In this way,
for instance, transport of the labelled material can be quantified
within living cells (Lippincott-Schwartz et al., 2003; LippincottSchwartz and Patterson, 2003).
FRET
Förster resonance energy transfer (FRET) occurs when two
fluorescent molecules come in close proximity to each other
(,5 nm or less), such that the donor fluorophore can transfer part
of the energy of its excited state via dipole–dipole interactions to
the acceptor fluorophore (Förster, 2012). Several distinct imaging
methods exist to quantify FRET in living cells, and they have been
extensively used to image biochemical reactions, such as protein–
protein interactions in living cells (Piston and Kremers, 2007; Zeug
et al., 2012).
FCS and FCCS
Fluorescence correlation spectroscopy (FCS) and fluorescence
cross-correlation spectroscopy (FCCS) are single-molecule
approaches that analyse the fluctuation of fluorescence in a
confocal volume that is usually generated by spot-laser
illumination of the sample in a microscope. FCS has been
mostly used to quantify the absolute number of molecules in a
volume, as well as their diffusive and non-diffusive dynamics
(Bacia et al., 2006; Chen et al., 2008). In comparison to FRAP,
FCS measurements need far fewer labelled molecules and, thus,
can measure molecule dynamics at concentrations that are close
to physiological expression levels and with reduced exposure to
light of the living cells under observation. In FCCS two types of
molecule are labelled with distinct fluorophores and their
fluctuations analysed within a confocal volume. If the two
molecules interact with each other they will move through the
volume simultaneously and generate a cross-correlation signal.
FCCS has been used to monitor protein–protein interactions in
living cells (Bacia et al., 2006).
Journal of Cell Science
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et al., 2006). This simple but elegant approach revealed that each
cisterna initially labelled by the cis-Golgi marker (green) changed
colour to the trans-Golgi marker (red), suggesting that Golgi
cisternae mature over time (Losev et al., 2006; Matsuura-Tokita
et al., 2006). These results are consistent with the Golgi maturation
model (Glick et al., 1997), which predicts that secretory cargo
moves through the Golgi complex in cisternae that form de novo,
mature from cis to trans, and then dissipate.
The examples above, which are by far not comprehensive owing
to space constraints, aim to illustrate certain fundamental
mechanistic aspects of ER-to-Golgi transport that would be very
difficult, or even impossible, to address without the direct
visualization of the factors involved inside living cells. However,
despite its great potential, this approach also has limitations. First,
in contrast to in vitro systems, where selected factors are combined
and their interactions or functions studied, any interpretation of
microscopy experiments in living cells has to deal with the
complexity of the entire cell and is therefore often difficult.
Second, when performing time-lapse-imaging experiments, the
possibility of cellular damage or the occurrence of artefacts due to
extensive exposure to fluorescence excitation light always exists
and is difficult to evaluate. Third, life cell imaging requires the
expression of a fluorescent marker in cells, which mostly is
achieved by tagging the protein of interest with fluorescent
proteins. This always bears the possibility that the tag changes the
natural behaviour of the protein. In addition, the expression levels
of FPs have to be controlled to ensure that cellular processes are
not disrupted and FPs reflect the behaviour of their endogenous
counterparts. Another problem is the difference in expression
levels among individual cells, which can be partially overcome
with the use of stably transfected cell lines. Physiological
expression levels may be obtained by driving the expression of
the cDNA under the control of the endogenous promotor of that
gene and flanking regulatory regions (Poser et al., 2008).
Resembling the well-established method for GFP expression in
yeasts cells (Howson et al., 2005), the endogenous gene may be
replaced by an FP version using the recently developed gene
replacement technology in mammalian tissue culture cells (Gaj
et al., 2012; Hauschild-Quintern et al., 2013; Santiago et al., 2008).
In summary, time-lapse imaging of FP in living cells has
helped to reveal many unexpected aspects of the spatiotemporal
organisation of ER-to-Golgi transport and the organelles
involved. However, owing to its limitations in resolving
structures below the diffraction of light, time-lapse fluorescence
microscopy is not able to provide information on the nature of, for
example, intra-Golgi transport, or the behaviour of COPI or
COPII transport vesicles at donor membranes or fusion with target
membranes. Similarly, molecular interactions of key regulators
and structural proteins operating in ER-to-Golgi transport cannot
be imaged by time-lapse fluorescence microscopy because of
limitations in resolution.
Imaging methods for advanced analyses of ERto-Golgi transport
To overcome the limitations of time-lapse fluorescence
microscopy several more advanced microscopy techniques have
been either re-discovered or newly developed in the past years.
proteins, as well as their interactions. Although, all F-techniques,
in principle, have a great potential to study the early secretory
pathway, mainly fluorescence recovery after photobleaching
(FRAP) and Förster resonance energy transfer (FRET)
measurements have been used to explore ER-to-Golgi transport.
FRAP has been developed initially to quantitatively determine,
using light microscopy, molecular dynamics such as diffusion in
membranes (Axelrod et al., 1976). Since the availability of
fluorescent proteins, this technology has been extensively used to
study the dynamics of GFP-tagged proteins in a semi-quantitative
manner and provided numerous new insights into the dynamic
organisation of the early secretory pathway (Lippincott-Schwartz
et al., 2003). For example, FRAP analyses of a temperaturesensitive mutant of the vesicular stomatitis virus glycoprotein
(VSVG), which is widely used as a marker for secretory cargo,
showed that the mobility of folded and unfolded protein within
the ER is similar and highly dynamic. These results suggested
that other mechanisms than protein immobilisation, for instance
interactions with chaperons, must be responsible for retention of
the unfolded protein in the ER (Nehls et al., 2000). More
advanced approaches that combine FRAP measurements and
mathematical models quantitatively describe the underlying
biochemical reactions responsible for the measured recovery
kinetics. This allows, for example, to determine the on- and offrates with which cytoplasmic proteins interact with organelles in
living cells (Sprague and McNally, 2005). Such modelling
approaches have also been used to obtain further insights into the
role of secretory cargo in the kinetics of the assembly of COPII
vesicular coat proteins at ERES (Forster et al., 2006) or COPI
vesicular coat proteins at Golgi membranes (Presley et al., 2002).
FRET is a non-radiative transfer of energy from an excited
donor fluorophore to an acceptor fluorophore in its proximity
(Fernandez and Berlin, 1976; Piston and Kremers, 2007; Zeug
et al., 2012) (see Box 1). As FRET signals strongly depend on the
distance between donor and acceptor fluorophore, this technique
has great potential to study the spatial organisation of protein–
protein interactions in ER-to-Golgi trafficking in living cells.
However, to our knowledge, the number of successful
applications of FRET measurements to address questions
related to ER-to-Golgi transport has been rather limited. FRET
measurements and confocal imaging demonstrated for the first
time in living cells that oligomerisation of G-protein-coupled
receptors occurs in the ER and in the Golgi, but the functional
significance of this process is still not clear (Herrick-Davis et al.,
2006). FRET measurements of fluorescently labelled KDEL
(Lys-Asp-Glu-Leu) receptor, the retrograde transport cargo
cholera toxin and COPI proteins could provide evidence for a
coupling of retrograde cargo-induced oligomerisation of the
KDEL receptor and its subsequent sorting into COPI vesicles
(Majoul et al., 2001). FRET measurements were also used to
investigate the kinetics of COPII coat complex assembly and
disassembly on artificial liposomes. This revealed that the COPII
pre-budding complex Sec23–Sec24 (see Table 1 for COPII
components) stays bound to cargo during multiple Sar1 GTPase
cycles, suggesting a model for the maintenance of kinetically
stable pre-budding complex that regulate cargo sorting into
COPII vesicles (Sato and Nakano, 2004).
F-techniques
EM
The so-called F-techniques (see Box 1) are able to characterise
quantitatively the diffusion and binding kinetics of fluorescent
Imaging organelles and membrane carriers of the early secretory
pathway by conventional fluorescence microscopy techniques is
Imaging ER-to-Golgi
Journal of Cell Science
Table 1. Minimal COPII and COPI components and their
respective roles
COPI
Arf 1
a COP
b COP
e COP
b9 COP
c COP
COP
f COP
GTPase
Outer or cage-like subcomplex
Outer or cage-like subcomplex
Outer or cage-like subcomplex
Inner or adaptor subcomplex
Inner or adaptor subcomplex
Inner or adaptor subcomplex
Inner or adaptor subcomplex
COPII
Sar1
Sec23
Sec24
Sec13 and Sec31
GTPase
Inner coat, GAP activity
Inner coat, cargo selection
Outer coat, membrane bending, increases GAP activity
limited by light diffraction, and structures that are smaller than
,250 nm in the xy-direction and 500 nm in the z-direction
cannot be resolved. To overcome this restriction and to obtain
information at the ultrastructural level, EM is the method of
choice. Unfortunately, it requires fixed cells and thus temporal
information on dynamic processes is difficult to obtain. In
specialised experimental set-ups, where transport can be
synchronised, e.g. by a shift in temperature or the addition of
chemical compounds, fixation of cells at different time-points
after the induction of transport can help to obtain temporal
information (Bonfanti et al., 1998; Marsh et al., 2004; Trucco
et al., 2004).
Combining such synchronised transport systems with electron
tomography, which allows volume imaging in EM and thus also
analyses of extended structures, showed that secretory cargo
induces the formation of tubules between Golgi cisternae and that
such tubular connections depend on the amount of cargo to be
transported (Marsh et al., 2004; San Pietro et al., 2009; Trucco
et al., 2004). Although these studies clearly demonstrated the
existence of such tubular connections in response to cargo waves,
it is not yet clear to which extent these Golgi tubules contribute to
intra-Golgi transport.
Another possible way to overcome the limitation of EM in
acquiring temporal information is to combine light and electron
microscopy to correlative light and electron microscopy (CLEM),
which first allows the visualisation of dynamic processes in
living cells, followed by ultra-structural analyses in the very same
fixed cells by EM (Mironov et al., 2000). One challenge when
using CLEM is to identify the very same cell or structure that was
observed by light microscopy for the subsequent imaging by EM.
Several variations of CLEM addressing this technical challenge
have been developed and used to investigate the early secretory
pathway. One approach uses photobleaching with the light
microscope to convert the fluorescent signal of interest into an
electron-dense diaminobenzidine (DAB) precipitate that can
subsequently be visualised using the electron microscope
(Grabenbauer et al., 2005). This method was applied to
visualise the Golgi and the ER (Gaietta et al., 2006;
Meisslitzer-Ruppitsch et al., 2009), and to identify intra-Golgi
COPI vesicles (Grabenbauer et al., 2005).
The structure and dynamics of formation of ER-to-Golgi
carriers have also been studied using CLEM combined with
tomography (Mironov et al., 2003). This study proposed that
larger saccular ER-to-Golgi transport carriers form in the vicinity
of COPII-coated ERES in a COPII-dependent manner without the
need of budding COPII-coated vesicles. This result has added a
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new perspective on how ER exit and subsequent transport in the
early secretory pathway might take place, and raised the question
to which extent such carriers, compared with COPII-coated
vesicles, mediate ER-to-Golgi transport. Immuno-electron
tomography analyses have, however, shown that free COPIIcoated vesicles and larger COPII-coated dumb-bell-shaped
tubules of 150–200 nm in size form at ER-exit sites (Zeuschner
et al., 2006). Further work, including rigorous quantification of
results, will be necessary to determine to which extent each of
these carriers observed during ER exit contribute to ER-to-Golgi
transport.
A further variation of CLEM was recently introduced to obtain
ultrastructural information regarding the dynamics of clathrincoated vesicle budding at the plasma membrane (Kukulski et al.,
2012). First, time-lapse fluorescence microscopy was used to
characterise the temporal association of fluorescently tagged
regulatory factors with newly forming endocytic vesicles
(Kaksonen et al., 2003; Kaksonen et al., 2005). This
information was then used to correlate the ultrastructure of
endocytic intermediates with protein dynamics of the regulatory
factors (Kukulski et al., 2012) (see Fig. 3A). Applying a similar
approach to study the early secretory pathway might help to
clarify important outstanding questions, such as the role of
regulators on the efficiency of the formation of COPII vesicles
and the homotypic fusion of these vesicles to form VTCs (see
Fig. 1), or the precise mechanisms of delivery of cargo at and
through the Golgi complex.
Super-resolution microscopy
New exciting light microscopy methods with a resolution below
the diffraction limit of conventional microscopes have been
developed in the past few years and were termed super-resolution
microscopy (see Box 2). These methods allow to image cells in
their native environment with a resolution that approaches the
one obtained with EM. Different approaches to resolve transport
carriers and structures that are relevant for ER-to-Golgi transport
exist. For example, in stimulated emission depletion (STED), the
excitation light to resolve structural details is spatially confined
(Hell and Wichmann, 1994) (see Box 2), which works well in
living cells and provides temporal resolutions that should allow
the imaging of COPII-coated ER-to-Golgi transport carriers with
a typical size between 60 and 80 nm. Accordingly, synaptic
vesicles and the ER have been imaged using STED (Hein et al.,
2008; Jones et al., 2011; Westphal et al., 2008; Willig et al.,
2006). However, thus far, STED has not provided any new
conceptual insights to ER-to-Golgi or intra-Golgi transport. One
possible reason for this might be that commercial STED systems
that are available to a broad community, although very powerful,
do not provide sufficient resolution in the z-direction and thus do
not allow to address questions regarding intra-Golgi transport
mechanisms, vesicle formation at the ER or formation of
vesicular tubular clusters (VTCs). Also, it should be noted that,
in contrast to EM, STED and other super-resolution microscopy
methods, do not provide information on the ultrastructural
cellular context of the molecules analysed. In order to achieve
this, multi-labelling of the samples to highlight cellular
landmarks next to the structures of interest would be necessary;
and this is still a challenge in super-resolution microscopy.
New approaches using structured illumination super-resolution
microscopy (SIM) (see Box 2) have been developed in the past
few years and come closer to fulfill the necessary requirements in
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Journal of Cell Science 126 (22)
A
i
iii
ii
Box 2. Super-resolution microscopy methods
iv
Fluorescence-microscopy-based imaging methods that overcome
the diffraction limit of light microscopes (,250 nm in xy direction
and ,500 nm in z direction) are referred to as super-resolution
microscopy techniques. They include structured illumination
microscopy (SIM), stimulated emission depletion (STED)
microscopy and localisation microscopy methods, such as
photoactivated localisation microscopy (PALM), stochastic
optical reconstruction microscopy (STORM) or ground-state
depletion microscopy followed by individual molecule return
(GSDIM). Several other comparable methods have been
developed, but are not discussed here owing to space constraints.
Journal of Cell Science
SIM
In SIM, a series of images with a stripe illumination at different,
well-defined positions are recorded. Analysis of the signal
variations between the different images allows to computationally
resolve structures with about twice the resolution in all axes
compared to conventional microscopy (Gustafsson, 2000;
Gustafsson, 2008). The method is well suited for life cell imaging
with all of the fluorescent labels currently available.
B
Fig. 3. Vesicular transport using CLEM and super-resolution
microscopy. (A) CLEM of yeast cells in different phases of endocytosis. The
upper two panels show an overlay of the fluorescently labelled endocytic
markers amphiphysin (Rvs167-GFP) and Abp1-mCherry expressed in S.
cerevisiae and prepared for EM. The fluorescent spots mark the occurrence of
endocytosis encircled by a dotted line. The combination of both fluorescent
markers allows to distinguish between an early endocytic event (yellow; i) or
a later endocytic event (red; ii). Scale bars: 2 mm. The two bottom images
below show virtual slices obtained from electron tomograms and show the
membrane ultrastructures that are found at the positions corresponding to the
encircled areas in i and ii. The left image (iii) shows an invagination (arrow),
suggesting the formation of an endocytic vesicle. The right image (iv) shows
an endocytic vesicle (arrow). Scale bars: 100 nm. (B) COPII and COPI
structures imaged using wide-field TIRF microscopy (left) and superresolution GSDIM (right). Fixed HeLa cells were immunostained for b-COP
(using Alexa-647-conjugated secondary antibody; red) and Sec31 (using
Alexa-532-conjugated antibody; green). COPI (arrowheads) and COPII
(arrows) structures that could not be resolved using TIRF were separated in
the super-resolution image that also allows the detection of different
substructure. Scale bar: 1 mm. Insets show an 4-fold magnification of the
areas between arrowheads and arrows.
order to image ER-to-Golgi transport. Rego and colleagues, by
adopting a non-linear SIM method and photo-switchable
fluorescent probes, were able to image cellular structures, such
as the nuclear pore and the actin cytoskeleton at a resolution of
50 nm (Rego et al., 2012). Other SIM approaches reached
100 nm resolution in 3D (Shao et al., 2008). More recent SIM
STED
In STED microscopy (Hell and Wichmann, 1994), a diffractionlimited excitation beam is superimposed by a donut-shaped STED
beam that, in comparison to the excitation beam, is red-shifted and
quenches excited molecules by stimulated emission depletion in
the periphery of the excitation focal spot. This way, resolutions as
low as 30 nm and the possibility of life cell imaging have been
reported (Westphal et al., 2008).
Localisation super-resolution microscopy
Localisation microscopy methods (Patterson et al., 2010) take
advantage of the possibility to localise single fluorescent
molecules at very high precision, down to the nanometer scale.
With these methods, fluorescent molecules, such as photoactivatable or photo-switchable fluorescent proteins, are
randomly switched on and imaged as single molecules by using
camera-based microscopy systems before they are switched off
again. Repeating this cycle up to several thousand times allows
the construction of super-resolution images of the fluorophore
distribution. Examples of current localisation techniques that
function on the basis of switching the observed fluorescent dyes
between their dark and bright states are, for instance, PALM
(Betzig et al., 2006; Hess et al., 2006), STORM (Rust et al., 2006)
or GSDIM (Fölling et al., 2008).
developments showed that it is possible to achieve two-colour 3D
imaging of clathrin-coated vesicles with a spatial resolution of
,120 nm (Fiolka et al., 2012). Although these exciting recent
developments indicate that SIM is a promising technique with
which to obtain multi-label life cell imaging using common
fluorophores, the spatial and temporal resolution of SIM systems
that are currently available to a larger community (,100–
150 nm) is not yet sufficient to allow life cell imaging of small
carriers, such as COPII- or COPI-coated vesicles with sufficient
temporal resolution that is necessary to track them during ER-toGolgi transport.
Another super-resolution approach uses stochastic singlemolecule localisation (here referred to as localisation
microscopy; see Box 1) (Lidke and Lidke, 2012; Patterson et al.,
2010; Sengupta et al., 2012; Toomre and Bewersdorf, 2010).
Photo-switchable or photo-activatable probes are used to generate
Journal of Cell Science
Imaging ER-to-Golgi
thousands of images, in which single molecules can be localised
with very high precision. These images are then used to reconstruct
the density labelling of the fluorescent marker of interest in the cell
with a resolution down to 10 nm (Patterson et al., 2010). A major
drawback of super-resolution localisation microscopy is that
imaging of fast events in the (sub)-second range, such as those
important in ER-to-Golgi transport, is difficult because the number
of single-molecule events that can be imaged within this timeframe is often not sufficient to allow a faithful reconstruction of the
distribution of the molecule of interest in living cells. However,
imaging of slowly moving structures, such as adhesion complexes
(Shroff et al., 2008), mitochondria, lysosomes or the ER (Shim
et al., 2012), by using stochastic super-resolution methods has been
demonstrated. Performance comparison of total internal reflection
fluorescence (TIRF) microscopy and the localisation microscopy
approach ground-state depletion microscopy followed by
individual molecule return (GSDIM) (see Box 2) in imaging
COPII and COPI structures at ERES is shown in Fig. 3B. Similar
to STED, initial attempts of using localisation microscopy had
their limits in that resolution in z-direction did not match the one
achieved in xy-direction. Recent developments, however, have
overcome these limitations and demonstrated studies localisation
microscopy applications with a significantly improved resolution
in z-direction (Huang et al., 2008; Shtengel et al., 2009; Xu et al.,
2012). Studies investigating the early secretory pathway might
benefit greatly from super-resolution imaging as this technique
may help to answer important outstanding questions, such as what
underlies formation, fission and fusion of transport vesicles or
carriers that have a role in the early secretory pathway, how are
organelles such as the Golgi complex organised, and what are the
links between transport vesicles and the microtubule cytoskeleton.
However, to address these questions, it will be necessary to
achieve the appropriate spatial and temporal resolution in life cell
super-resolution imaging. As some transports carriers involved in
ER-to-Golgi transport are only between 60 and 80 nm, and need to
be tracked at a sub-second resolution, life cell super-resolution
imaging remains a challenge to study ER-to-Golgi transport.
Imaging ER-to-Golgi transport at the systems
level
As mentioned above, imaging ER-to-Golgi transport by using
different microscopy techniques in living cells has revealed its
dynamic nature and led to the proposal of new concepts with
regard to the organization of the early secretory pathway.
However, the imaging approaches used to reveal these new
concepts, such as time-lapse imaging or FRAP analyses, have
only contributed to a limited extent to the identification or
characterization of factors that regulate the early secretory
pathway at the systems level. To understand the early secretory
pathway at the systems level, including its regulation by
responses to e.g. extracellular stimuli or differentiation
processes, it is necessary to first identify the factors involved in
a comprehensive manner. Once this is achieved, it is important to
quantitatively determine how and when these factors interact
with each other in order to formulate a quantitative model that
describes the regulation of the early secretory pathway.
In a first step towards this goal, proteomic approaches were
used to comprehensively identify secreted proteins as well as
proteins of the organelles that encompass the secretory pathway
(Gannon et al., 2011; Gilchrist et al., 2006; Meissner et al., 2013).
However, these approaches require biochemical purification of
5097
the organelles, which removes them from their cellular context
and, therefore, the proteins identified in such studies may not
represent all the proteins that associate with the secretory
pathway and related organelles in unperturbed intact cells.
Systematic localisation and unbiased functional characterisation
of uncharacterised GFP-tagged human cDNAs in living cells have
been used as an alternative to identify potential new regulators of the
early secretory pathway (Simpson et al., 2000; Starkuviene et al.,
2004; Starkuviene and Pepperkok, 2007). The involvement of a
gene in the early secretory pathway can also be investigated in intact
cells, by knocking it down using RNA interference (RNAi) and
analysing the effect on trafficking and/or the morphology of the
secretory pathway components. A number of such RNAi-based
screens have been performed in metazoans (Bard et al., 2006;
D’Ambrosio and Vale, 2010; Farhan et al., 2010; Kondylis et al.,
2011; Simpson et al., 2012; Wendler et al., 2010). For example, two
genome-wide screens identified new genes with a role in protein
secretion by first analysing the effects of gene knockdown on
protein secretion by using enzymatic bulk readout analysis, followed
by systematic microscopy-based analyses to better understand the
role of the identified genes in regulating the early secretory pathway
or Golgi integrity (Bard et al., 2006; Wendler et al., 2010).
To achieve quantitative systematic analyses in high-throughput
microscopy, all steps of the experiment, including sample
preparation, image acquisition and single-cell quantitative
analyses need to be automated and integrated (Pepperkok and
Ellenberg, 2006). Such an automated, integrated approach has
recently been used to identify, at genome level, those genes that,
when knocked down, cause alterations in biosynthetic protein
trafficking (Simpson et al., 2012) and organelle integrity (Farhan
et al., 2010; Kondylis et al., 2011; Simpson et al., 2012). Farhan
and colleagues investigated the role of human kinases and
phosphatases in the distribution of membrane markers of the
early secretory pathway, and showed that growth factor signalling
regulates ER export through ERK2. Besides the MAPK signalling
pathway, a number of other signalling networks, such as those
involving insulin, phosphatidylinositol or toll-like receptor
signalling, were also found to have a role in the regulation of the
early secretory pathway (Farhan et al., 2010).
Using a genome-wide RNAi screen, Simpson and colleagues
showed that several GTPases and GTPase-binding proteins have
a role in the regulation of ER-to-Golgi transport and organelle
integrity (Simpson et al., 2012). Moreover, their work showed
that EGF-mediated signalling from the cell surface regulates the
efficiency of ER-exit, as demonstrated by knockdown of the
components of a network consisting of EGF signalling factors
and the EGF receptor (Simpson et al., 2012). Similarly, a recent
RNAi screen in Drosophila S2 cells that targeted over 100 genes
that had been selected using bioinformatics has shown a potential
link between the early secretory pathway and cell metabolism
(Kondylis et al., 2011).
Together, these systematic analyses using high-throughput
microscopy suggest that the regulation of the secretory pathway
is tightly coupled to other cellular processes at multiple levels and
that only an in vivo approach will be able to unveil these networks
and regulatory processes. The genes that, in these various RNAi
screens, were shown to be involved in the regulation of the early
secretory pathway represent an excellent basis for follow-up
studies to further investigate their role and mechanism of action.
The first step to achieve this might be high-throughput microscopy
in living cells at large scale, to evaluate the effect of gene
5098
Journal of Cell Science 126 (22)
Journal of Cell Science
knockdown on the dynamics of transport and organelle alteration
at the boundary between ER and Golgi, similarly to what has been
demonstrated for the endocytic pathway and cell division (Collinet
et al., 2010; Neumann et al., 2010).
Future perspectives
Sequencing of the complete human genome gave biologists a
better understanding of cellular processes and their regulation at a
systems level. The option to express fluorescent proteins and
fluorescent probes allows to visualise almost any cellular structure
by using fluorescence microscopy in living cells and to access
proteins in their natural environment, thereby providing temporal
and spatial information of their function (Pepperkok and Ellenberg,
2006). Although these approaches, together with correlative light
and electron microscopy analyses have, indeed, changed our view
on the dynamics and molecular organisation of the early secretory
pathway, many future challenges and opportunities remain. One of
them will be to develop robust tools to image lipids in living cells.
Owing to the lack of such tools in the past, our knowledge of the
role of lipids in the early secretory pathway is fairly limited. Which
lipids at what concentration, facilitate the formation of tubular or
vesicular carriers or participate in regulating ER-to-Golgi transport
remain open questions.
One possible way to image the distribution and dynamics of
lipids indirectly is the use of fluorescently labelled proteins with
a lipid-binding domain that specifically recognises a particular
class of lipids, such as inositides, diacylglycerol or
phosphatidylserine (Sarantis and Grinstein, 2012; Schultz,
2010). Using this approach, in combination with biochemical
analysis, has revealed that PtdIns(4)P is required for Golgi
integrity and protein sorting (Piao and Mayinger, 2012) and that
it might also have a role in the formation of ERES (BlumentalPerry et al., 2006). To improve this indirect approach to image
lipids under non-physiological conditions, it will be necessary to
use living cells and directly label lipids under conditions as
similar as possible to physiological conditions (Schultz, 2010).
Strategies of chemical biology, which involve organic synthesis
of the lipid of interest, have been developed (Mentel et al., 2011;
Schultz et al., 2010) and demonstrated recently that PtdIns(3)P
induces fusion of early endosomes (Subramanian et al., 2010).
Combining life cell imaging techniques with other methods,
such as RNAi, small-molecule-based perturbation, overexpression
analysis or subtle cell manipulation such as laser nanosurgery, can
result in an invaluable amount of quantitative information. Recent
developments of super-resolution microscopy to life cell imaging,
3D and improved speed of data acquisition (Dedecker et al., 2012;
Eggeling et al., 2013; Gao et al., 2012; Hein et al., 2008; Lidke and
Lidke, 2012; Planchon et al., 2011; Shim et al., 2012; York et al.,
2011), might make it possible to image the molecular organisation
of the early secretory pathway in living cells at so-far unmatched
resolution.
Moreover, the combination of super-resolution microscopy
with other methods, such as FRET (Cho et al., 2013) or
correlative life cell imaging (Bálint et al., 2013), might reveal
details of intra-Golgi transport or the formation of transport
carriers for large cargo at ERES that, to date, cannot be accessed
owing to the resolution limits of conventional fluorescence timelapse microscopy. Until now, quantitative high-throughput
imaging in living cells at the genome scale has only been
achieved in a few cases (Collinet et al., 2010; Neumann et al.,
2010) and remains technically challenging. However, availability
of the technology and the success of these studies in revealing
quantitative descriptions of phenotypes on the basis of organelle
and molecule dynamics in a comprehensive manner will certainly
stimulate its application to other biological questions, such as the
organisation and regulation of the early secretory pathway.
Extending high-throughput imaging to include FRAP, FRET or
super-resolution microscopy analyses of the early secretory
pathway is still very challenging; however, it has great potential
in providing comprehensive and quantitative understanding of how
the early secretory pathway is regulated. The foundations to
achieve this goal have already been laid with the recent
development that allows feedback-control of microscopes
(Conrad et al., 2011; Tsukada and Hashimoto, 2013), as well as
with automatic high-throughput FRAP analyses on specific
cellular structures as that are automatically recognised by online
image analysis (Conrad et al., 2011). With such systematic
quantitative data sets at hands, we anticipate that it is possible to
draft the first quantitative models of the protein networks that
underlie the molecular organisation of the early secretory pathway.
Acknowledgements
We thank Wanda Kukulski, Marko Kaksonen and John Briggs
(EMBL, Heidelberg, Germany) for providing Fig. 3A, and Stefan
Terjung (EMBL, Heidelberg, Germany) for acquiring the data for
Fig. 3B. We apologise to all colleagues whose work was not cited
due to space restrictions.
Funding
F.V. and R.P. are supported by an EU Systems Microscopy network
of excellence grant FP7/2007-2013-258068.
Supplementary material available online at
http://jcs.biologists.org/lookup/suppl/doi:10.1242/jcs.121061/-/DC1
References
Appenzeller-Herzog, C. and Hauri, H. P. (2006). The ER-Golgi intermediate
compartment (ERGIC): in search of its identity and function. J. Cell Sci. 119,
2173-2183.
Axelrod, D., Koppel, D. E., Schlessinger, J., Elson, E. and Webb, W. W. (1976).
Mobility measurement by analysis of fluorescence photobleaching recovery kinetics.
Biophys. J. 16, 1055-1069.
Bacia, K., Kim, S. A. and Schwille, P. (2006). Fluorescence cross-correlation
spectroscopy in living cells. Nat. Methods 3, 83-89.
Bálint, S., Verdeny Vilanova, I., Sandoval Álvarez, A. and Lakadamyali, M. (2013).
Correlative live-cell and superresolution microscopy reveals cargo transport dynamics
at microtubule intersections. Proc. Natl. Acad. Sci. USA 110, 3375-3380.
Bard, F., Casano, L., Mallabiabarrena, A., Wallace, E., Saito, K., Kitayama, H.,
Guizzunti, G., Hu, Y., Wendler, F., Dasgupta, R. et al. (2006). Functional
genomics reveals genes involved in protein secretion and Golgi organization. Nature
439, 604-607.
Barlowe, C., Orci, L., Yeung, T., Hosobuchi, M., Hamamoto, S., Salama, N.,
Rexach, M. F., Ravazzola, M., Amherdt, M. and Schekman, R. (1994). COPII: a
membrane coat formed by Sec proteins that drive vesicle budding from the
endoplasmic reticulum. Cell 77, 895-907.
Ben-Tekaya, H., Miura, K., Pepperkok, R. and Hauri, H. P. (2005). Live imaging of
bidirectional traffic from the ERGIC. J. Cell Sci. 118, 357-367.
Béthune, J., Wieland, F. and Moelleken, J. (2006). COPI-mediated transport.
J. Membr. Biol. 211, 65-79.
Betzig, E., Patterson, G. H., Sougrat, R., Lindwasser, O. W., Olenych, S.,
Bonifacino, J. S., Davidson, M. W., Lippincott-Schwartz, J. and Hess, H. F.
(2006). Imaging intracellular fluorescent proteins at nanometer resolution. Science
313, 1642-1645.
Bevis, B. J., Hammond, A. T., Reinke, C. A. and Glick, B. S. (2002). De novo
formation of transitional ER sites and Golgi structures in Pichia pastoris. Nat. Cell
Biol. 4, 750-756.
Blumental-Perry, A., Haney, C. J., Weixel, K. M., Watkins, S. C., Weisz, O. A. and
Aridor, M. (2006). Phosphatidylinositol 4-phosphate formation at ER exit sites
regulates ER export. Dev. Cell 11, 671-682.
Bonfanti, L., Mironov, A. A., Jr, Martı́nez-Menárguez, J. A., Martella, O., Fusella,
A., Baldassarre, M., Buccione, R., Geuze, H. J., Mironov, A. A. and Luini,
A. (1998). Procollagen traverses the Golgi stack without leaving the lumen of
cisternae: evidence for cisternal maturation. Cell 95, 993-1003.
Journal of Cell Science
Imaging ER-to-Golgi
Brandizzi, F. and Barlowe, C. (2013). Organization of the ER-Golgi interface for
membrane traffic control. Nat. Rev. Mol. Cell Biol. 14, 382-392.
Chen, H., Farkas, E. R. and Webb, W. W. (2008). Chapter 1: In vivo applications of
fluorescence correlation spectroscopy. Methods Cell Biol. 89, 3-35.
Cho, S., Jang, J., Song, C., Lee, H., Ganesan, P., Yoon, T. Y., Kim, M. W., Choi,
M. C., Ihee, H., Do Heo, W. et al. (2013). Simple super-resolution live-cell imaging
based on diffusion-assisted Förster resonance energy transfer. Sci. Rep. 3, 1208.
Collinet, C., Stöter, M., Bradshaw, C. R., Samusik, N., Rink, J. C., Kenski, D.,
Habermann, B., Buchholz, F., Henschel, R., Mueller, M. S. et al. (2010). Systems
survey of endocytosis by multiparametric image analysis. Nature 464, 243-249.
Conrad, C., Wünsche, A., Tan, T. H., Bulkescher, J., Sieckmann, F., Verissimo, F.,
Edelstein, A., Walter, T., Liebel, U., Pepperkok, R. et al. (2011). Micropilot:
automation of fluorescence microscopy-based imaging for systems biology. Nat.
Methods 8, 246-249.
Crivat, G. and Taraska, J. W. (2012). Imaging proteins inside cells with fluorescent
tags. Trends Biotechnol. 30, 8-16.
D’Ambrosio, M. V. and Vale, R. D. (2010). A whole genome RNAi screen of
Drosophila S2 cell spreading performed using automated computational image
analysis. J. Cell Biol. 191, 471-478.
Dancourt, J. and Barlowe, C. (2010). Protein sorting receptors in the early secretory
pathway. Annu. Rev. Biochem. 79, 777-802.
Dedecker, P., Mo, G. C., Dertinger, T. and Zhang, J. (2012). Widely accessible
method for superresolution fluorescence imaging of living systems. Proc. Natl. Acad.
Sci. USA 109, 10909-10914.
Eggeling, C., Willig, K. I. and Barrantes, F. J. (2013). STED microscopy of living
cells—new frontiers in membrane and neurobiology. J. Neurochem. 126, 203-212.
Farhan, H., Wendeler, M. W., Mitrovic, S., Fava, E., Silberberg, Y., Sharan, R.,
Zerial, M. and Hauri, H. P. (2010). MAPK signaling to the early secretory pathway
revealed by kinase/phosphatase functional screening. J. Cell Biol. 189, 997-1011.
Fernandez, S. M. and Berlin, R. D. (1976). Cell surface distribution of lectin receptors
determined by resonance energy transfer. Nature 264, 411-415.
Fiolka, R., Shao, L., Rego, E. H., Davidson, M. W. and Gustafsson, M. G. (2012).
Time-lapse two-color 3D imaging of live cells with doubled resolution using
structured illumination. Proc. Natl. Acad. Sci. USA 109, 5311-5315.
Fölling, J., Bossi, M., Bock, H., Medda, R., Wurm, C. A., Hein, B., Jakobs, S.,
Eggeling, C. and Hell, S. W. (2008). Fluorescence nanoscopy by ground-state
depletion and single-molecule return. Nat. Methods 5, 943-945.
Förster, T. (2012). Energy migration and fluorescence. 1946. J. Biomed. Opt. 17,
011002.
Forster, R., Weiss, M., Zimmermann, T., Reynaud, E. G., Verissimo, F., Stephens,
D. J. and Pepperkok, R. (2006). Secretory cargo regulates the turnover of COPII
subunits at single ER exit sites. Curr. Biol. 16, 173-179.
Fries, E. and Rothman, J. E. (1980). Transport of vesicular stomatitis virus
glycoprotein in a cell-free extract. Proc. Natl. Acad. Sci. USA 77, 3870-3874.
Gaietta, G. M., Giepmans, B. N., Deerinck, T. J., Smith, W. B., Ngan, L., Llopis, J.,
Adams, S. R., Tsien, R. Y. and Ellisman, M. H. (2006). Golgi twins in late mitosis
revealed by genetically encoded tags for live cell imaging and correlated electron
microscopy. Proc. Natl. Acad. Sci. USA 103, 17777-17782.
Gaj, T., Guo, J., Kato, Y., Sirk, S. J. and Barbas, C. F., 3rd (2012). Targeted gene
knockout by direct delivery of zinc-finger nuclease proteins. Nat. Methods 9, 805-807.
Gannon, J., Bergeron, J. J. and Nilsson, T. (2011). Golgi and related vesicle
proteomics: simplify to identify. Cold Spring Harb. Perspect. Biol. 3.
Gao, L., Shao, L., Higgins, C. D., Poulton, J. S., Peifer, M., Davidson, M. W., Wu,
X., Goldstein, B. and Betzig, E. (2012). Noninvasive imaging beyond the diffraction
limit of 3D dynamics in thickly fluorescent specimens. Cell 151, 1370-1385.
Giepmans, B. N., Adams, S. R., Ellisman, M. H. and Tsien, R. Y. (2006). The
fluorescent toolbox for assessing protein location and function. Science 312, 217-224.
Gilchrist, A., Au, C. E., Hiding, J., Bell, A. W., Fernandez-Rodriguez, J., Lesimple,
S., Nagaya, H., Roy, L., Gosline, S. J., Hallett, M. et al. (2006). Quantitative
proteomics analysis of the secretory pathway. Cell 127, 1265-1281.
Glick, B. S., Elston, T. and Oster, G. (1997). A cisternal maturation mechanism can
explain the asymmetry of the Golgi stack. FEBS Lett. 414, 177-181.
Grabenbauer, M., Geerts, W. J., Fernadez-Rodriguez, J., Hoenger, A., Koster, A. J.
and Nilsson, T. (2005). Correlative microscopy and electron tomography of GFP
through photooxidation. Nat. Methods 2, 857-862.
Gürkan, C., Stagg, S. M., Lapointe, P. and Balch, W. E. (2006). The COPII cage:
unifying principles of vesicle coat assembly. Nat. Rev. Mol. Cell Biol. 7, 727-738.
Gustafsson, M. G. (2000). Surpassing the lateral resolution limit by a factor of two
using structured illumination microscopy. J. Microsc. 198, 82-87.
Gustafsson, M. G. (2008). Super-resolution light microscopy goes live. Nat. Methods 5,
385-387.
Hauschild-Quintern, J., Petersen, B., Cost, G. J. and Niemann, H. (2013). Gene
knockout and knockin by zinc-finger nucleases: current status and perspectives. Cell.
Mol. Life Sci. 70, 2969-2983.
Hein, B., Willig, K. I. and Hell, S. W. (2008). Stimulated emission depletion (STED)
nanoscopy of a fluorescent protein-labeled organelle inside a living cell. Proc. Natl.
Acad. Sci. USA 105, 14271-14276.
Hell, S. W. and Wichmann, J. (1994). Breaking the diffraction resolution limit by
stimulated emission: stimulated-emission-depletion fluorescence microscopy. Opt.
Lett. 19, 780-782.
Herpers, B. and Rabouille, C. (2004). mRNA localization and ER-based protein sorting
mechanisms dictate the use of transitional endoplasmic reticulum-golgi units involved
in gurken transport in Drosophila oocytes. Mol. Biol. Cell 15, 5306-5317.
5099
Herrick-Davis, K., Weaver, B. A., Grinde, E. and Mazurkiewicz, J. E. (2006).
Serotonin 5-HT2C receptor homodimer biogenesis in the endoplasmic reticulum:
real-time visualization with confocal fluorescence resonance energy transfer. J. Biol.
Chem. 281, 27109-27116.
Hess, S. T., Girirajan, T. P. and Mason, M. D. (2006). Ultra-high resolution imaging
by fluorescence photoactivation localization microscopy. Biophys. J. 91, 4258-4272.
Howson, R., Huh, W. K., Ghaemmaghami, S., Falvo, J. V., Bower, K., Belle, A.,
Dephoure, N., Wykoff, D. D., Weissman, J. S. and O’Shea, E. K. (2005).
Construction, verification and experimental use of two epitope-tagged collections of
budding yeast strains. Comp. Funct. Genomics 6, 2-16.
Hsu, V. W. and Yang, J. S. (2009). Mechanisms of COPI vesicle formation. FEBS Lett.
583, 3758-3763.
Huang, B., Wang, W., Bates, M. and Zhuang, X. (2008). Three-dimensional superresolution imaging by stochastic optical reconstruction microscopy. Science 319, 810-813.
Hughes, H. and Stephens, D. J. (2008). Assembly, organization, and function of the
COPII coat. Histochem. Cell Biol. 129, 129-151.
Huh, W. K., Falvo, J. V., Gerke, L. C., Carroll, A. S., Howson, R. W., Weissman,
J. S. and O’Shea, E. K. (2003). Global analysis of protein localization in budding
yeast. Nature 425, 686-691.
Jamieson, J. D. and Palade, G. E. (1967). Intracellular transport of secretory proteins in
the pancreatic exocrine cell. I. Role of the peripheral elements of the Golgi complex.
J. Cell Biol. 34, 577-596.
Jamieson, J. D. and Palade, G. E. (1968). Intracellular transport of secretory proteins in
the pancreatic exocrine cell. 3. Dissociation of intracellular transport from protein
synthesis. J. Cell Biol. 39, 580-588.
Jones, S. A., Shim, S. H., He, J. and Zhuang, X. (2011). Fast, three-dimensional superresolution imaging of live cells. Nat. Methods 8, 499-505.
Kaksonen, M., Sun, Y. and Drubin, D. G. (2003). A pathway for association of
receptors, adaptors, and actin during endocytic internalization. Cell 115, 475-487.
Kaksonen, M., Toret, C. P. and Drubin, D. G. (2005). A modular design for the
clathrin- and actin-mediated endocytosis machinery. Cell 123, 305-320.
Kondylis, V., Tang, Y., Fuchs, F., Boutros, M. and Rabouille, C. (2011).
Identification of ER proteins involved in the functional organisation of the early
secretory pathway in Drosophila cells by a targeted RNAi screen. PLoS ONE 6,
e17173.
Kukulski, W., Schorb, M., Kaksonen, M. and Briggs, J. A. (2012). Plasma membrane
reshaping during endocytosis is revealed by time-resolved electron tomography. Cell
150, 508-520.
Lee, M. C., Miller, E. A., Goldberg, J., Orci, L. and Schekman, R. (2004). Bi-directional
protein transport between the ER and Golgi. Annu. Rev. Cell Dev. Biol. 20, 87-123.
Lidke, D. S. and Lidke, K. A. (2012). Advances in high-resolution imaging—techniques
for three-dimensional imaging of cellular structures. J. Cell Sci. 125, 2571-2580.
Lippincott-Schwartz, J. and Liu, W. (2006). Insights into COPI coat assembly and
function in living cells. Trends Cell Biol. 16, e1-e4.
Lippincott-Schwartz, J. and Patterson, G. H. (2003). Development and use of
fluorescent protein markers in living cells. Science 300, 87-91.
Lippincott-Schwartz, J., Altan-Bonnet, N. and Patterson, G. H. (2003).
Photobleaching and photoactivation: following protein dynamics in living cells.
Nat. Cell Biol. Suppl, S7-S14.
Losev, E., Reinke, C. A., Jellen, J., Strongin, D. E., Bevis, B. J. and Glick, B. S.
(2006). Golgi maturation visualized in living yeast. Nature 441, 1002-1006.
Majoul, I., Straub, M., Hell, S. W., Duden, R. and Söling, H. D. (2001). KDEL-cargo
regulates interactions between proteins involved in COPI vesicle traffic: measurements
in living cells using FRET. Dev. Cell 1, 139-153.
Marsh, B. J., Volkmann, N., McIntosh, J. R. and Howell, K. E. (2004). Direct
continuities between cisternae at different levels of the Golgi complex in glucose-stimulated
mouse islet beta cells. Proc. Natl. Acad. Sci. USA 101, 5565-5570.
Matsuura-Tokita, K., Takeuchi, M., Ichihara, A., Mikuriya, K. and Nakano,
A. (2006). Live imaging of yeast Golgi cisternal maturation. Nature 441, 1007-1010.
Meisslitzer-Ruppitsch, C., Röhrl, C., Neumüller, J., Pavelka, M. and Ellinger,
A. (2009). Photooxidation technology for correlated light and electron microscopy.
J. Microsc. 235, 322-335.
Meissner, F., Scheltema, R. A., Mollenkopf, H. J. and Mann, M. (2013). Direct proteomic
quantification of the secretome of activated immune cells. Science 340, 475-478.
Mentel, M., Laketa, V., Subramanian, D., Gillandt, H. and Schultz, C. (2011).
Photoactivatable and cell-membrane-permeable phosphatidylinositol 3,4,5-trisphosphate.
Angew. Chem. Int. Ed. Engl. 50, 3811-3814.
Mironov, A. A., Polishchuk, R. S. and Luini, A. (2000). Visualizing membrane traffic
in vivo by combined video fluorescence and 3D electron microscopy. Trends Cell
Biol. 10, 349-353.
Mironov, A. A., Mironov, A. A., Jr, Beznoussenko, G. V., Trucco, A., Lupetti, P.,
Smith, J. D., Geerts, W. J., Koster, A. J., Burger, K. N., Martone, M. E. et al.
(2003). ER-to-Golgi carriers arise through direct en bloc protrusion and multistage
maturation of specialized ER exit domains. Dev. Cell 5, 583-594.
Murshid, A. and Presley, J. F. (2004). ER-to-Golgi transport and cytoskeletal
interactions in animal cells. Cell. Mol. Life Sci. 61, 133-145.
Nehls, S., Snapp, E. L., Cole, N. B., Zaal, K. J., Kenworthy, A. K., Roberts, T. H.,
Ellenberg, J., Presley, J. F., Siggia, E. and Lippincott-Schwartz, J. (2000).
Dynamics and retention of misfolded proteins in native ER membranes. Nat. Cell
Biol. 2, 288-295.
Neumann, B., Walter, T., Hériché, J. K., Bulkescher, J., Erfle, H., Conrad, C., Rogers,
P., Poser, I., Held, M., Liebel, U. et al. (2010). Phenotypic profiling of the human
genome by time-lapse microscopy reveals cell division genes. Nature 464, 721-727.
Journal of Cell Science
5100
Journal of Cell Science 126 (22)
O’Rourke, N. A., Meyer, T. and Chandy, G. (2005). Protein localization studies in the
age of ‘Omics’. Curr. Opin. Chem. Biol. 9, 82-87.
Palade, G. (1975). Intracellular aspects of the process of protein synthesis. Science 189,
867.
Patterson, G., Davidson, M., Manley, S. and Lippincott-Schwartz, J. (2010).
Superresolution imaging using single-molecule localization. Annu. Rev. Phys. Chem.
61, 345-367.
Pepperkok, R. and Ellenberg, J. (2006). High-throughput fluorescence microscopy for
systems biology. Nat. Rev. Mol. Cell Biol. 7, 690-696.
Piao, H. and Mayinger, P. (2012). Growth and metabolic control of lipid signalling at
the Golgi. Biochem. Soc. Trans. 40, 205-209.
Piston, D. W. and Kremers, G. J. (2007). Fluorescent protein FRET: the good, the bad
and the ugly. Trends Biochem. Sci. 32, 407-414.
Planchon, T. A., Gao, L., Milkie, D. E., Davidson, M. W., Galbraith, J. A.,
Galbraith, C. G. and Betzig, E. (2011). Rapid three-dimensional isotropic imaging
of living cells using Bessel beam plane illumination. Nat. Methods 8, 417-423.
Poser, I., Sarov, M., Hutchins, J. R., Hériché, J. K., Toyoda, Y., Pozniakovsky, A.,
Weigl, D., Nitzsche, A., Hegemann, B., Bird, A. W. et al. (2008). BAC
TransgeneOmics: a high-throughput method for exploration of protein function in
mammals. Nat. Methods 5, 409-415.
Presley, J. F., Cole, N. B., Schroer, T. A., Hirschberg, K., Zaal, K. J. and LippincottSchwartz, J. (1997). ER-to-Golgi transport visualized in living cells. Nature 389, 81-85.
Presley, J. F., Ward, T. H., Pfeifer, A. C., Siggia, E. D., Phair, R. D. and LippincottSchwartz, J. (2002). Dissection of COPI and Arf1 dynamics in vivo and role in Golgi
membrane transport. Nature 417, 187-193.
Preuss, D., Mulholland, J., Franzusoff, A., Segev, N. and Botstein, D. (1992).
Characterization of the Saccharomyces Golgi complex through the cell cycle by
immunoelectron microscopy. Mol. Biol. Cell 3, 789-803.
Rego, E. H., Shao, L., Macklin, J. J., Winoto, L., Johansson, G. A., Kamps-Hughes,
N., Davidson, M. W. and Gustafsson, M. G. (2012). Nonlinear structuredillumination microscopy with a photoswitchable protein reveals cellular structures at
50-nm resolution. Proc. Natl. Acad. Sci. USA 109, E135-E143.
Rossanese, O. W., Soderholm, J., Bevis, B. J., Sears, I. B., O’Connor, J.,
Williamson, E. K. and Glick, B. S. (1999). Golgi structure correlates with
transitional endoplasmic reticulum organization in Pichia pastoris and Saccharomyces
cerevisiae. J. Cell Biol. 145, 69-81.
Rothman, J. E. (1996). The protein machinery of vesicle budding and fusion. Protein
Sci. 5, 185-194.
Rust, M. J., Bates, M. and Zhuang, X. (2006). Sub-diffraction-limit imaging by
stochastic optical reconstruction microscopy (STORM). Nat. Methods 3, 793-795.
San Pietro, E., Capestrano, M., Polishchuk, E. V., DiPentima, A., Trucco, A., Zizza,
P., Mariggiò, S., Pulvirenti, T., Sallese, M., Tete, S. et al. (2009). Group IV
phospholipase A(2)alpha controls the formation of inter-cisternal continuities
involved in intra-Golgi transport. PLoS Biol. 7, e1000194.
Santiago, Y., Chan, E., Liu, P. Q., Orlando, S., Zhang, L., Urnov, F. D., Holmes,
M. C., Guschin, D., Waite, A., Miller, J. C. et al. (2008). Targeted gene knockout in
mammalian cells by using engineered zinc-finger nucleases. Proc. Natl. Acad. Sci.
USA 105, 5809-5814.
Sarantis, H. and Grinstein, S. (2012). Monitoring phospholipid dynamics during
phagocytosis: application of genetically-encoded fluorescent probes. Methods Cell
Biol. 108, 429-444.
Sato, K. and Nakano, A. (2004). Reconstitution of coat protein complex II (COPII)
vesicle formation from cargo-reconstituted proteoliposomes reveals the potential role
of GTP hydrolysis by Sar1p in protein sorting. J. Biol. Chem. 279, 1330-1335.
Scales, S. J., Pepperkok, R. and Kreis, T. E. (1997). Visualization of ER-to-Golgi
transport in living cells reveals a sequential mode of action for COPII and COPI. Cell
90, 1137-1148.
Schultz, C. (2010). Challenges in studying phospholipid signaling. Nat. Chem. Biol. 6,
473-475.
Schultz, C., Neef, A. B., Gadella, T. W., Jr and Goedhart, J. (2010). Imaging lipids in
living cells. Cold Spring Harbor Protocols 2010, top83.
Sengupta, P., Van Engelenburg, S. and Lippincott-Schwartz, J. (2012). Visualizing
cell structure and function with point-localization superresolution imaging. Dev. Cell
23, 1092-1102.
Shaner, N. C., Steinbach, P. A. and Tsien, R. Y. (2005). A guide to choosing
fluorescent proteins. Nat. Methods 2, 905-909.
Shao, L., Isaac, B., Uzawa, S., Agard, D. A., Sedat, J. W. and Gustafsson, M. G.
(2008). I5S: wide-field light microscopy with 100-nm-scale resolution in three
dimensions. Biophys. J. 94, 4971-4983.
Shim, S. H., Xia, C., Zhong, G., Babcock, H. P., Vaughan, J. C., Huang, B., Wang,
X., Xu, C., Bi, G. Q. and Zhuang, X. (2012). Super-resolution fluorescence imaging
of organelles in live cells with photoswitchable membrane probes. Proc. Natl. Acad.
Sci. USA 109, 13978-13983.
Shima, D. T., Cabrera-Poch, N., Pepperkok, R. and Warren, G. (1998). An ordered
inheritance strategy for the Golgi apparatus: visualization of mitotic disassembly
reveals a role for the mitotic spindle. J. Cell Biol. 141, 955-966.
Shima, D. T., Scales, S. J., Kreis, T. E. and Pepperkok, R. (1999). Segregation of
COPI-rich and anterograde-cargo-rich domains in endoplasmic-reticulum-to-Golgi
transport complexes. Curr. Biol. 9, 821-824.
Shroff, H., Galbraith, C. G., Galbraith, J. A. and Betzig, E. (2008). Live-cell
photoactivated localization microscopy of nanoscale adhesion dynamics. Nat.
Methods 5, 417-423.
Shtengel, G., Galbraith, J. A., Galbraith, C. G., Lippincott-Schwartz, J., Gillette,
J. M., Manley, S., Sougrat, R., Waterman, C. M., Kanchanawong, P., Davidson,
M. W. et al. (2009). Interferometric fluorescent super-resolution microscopy resolves
3D cellular ultrastructure. Proc. Natl. Acad. Sci. USA 106, 3125-3130.
Simpson, J. C., Wellenreuther, R., Poustka, A., Pepperkok, R. and Wiemann, S.
(2000). Systematic subcellular localization of novel proteins identified by large-scale
cDNA sequencing. EMBO Rep. 1, 287-292.
Simpson, J. C., Joggerst, B., Laketa, V., Verissimo, F., Cetin, C., Erfle, H., Bexiga,
M. G., Singan, V. R., Hériché, J. K., Neumann, B. et al. (2012). Genome-wide
RNAi screening identifies human proteins with a regulatory function in the early
secretory pathway. Nat. Cell Biol. 14, 764-774.
Sprague, B. L. and McNally, J. G. (2005). FRAP analysis of binding: proper and
fitting. Trends Cell Biol. 15, 84-91.
Starkuviene, V. and Pepperkok, R. (2007). Differential requirements for ts-O45-G and
procollagen biosynthetic transport. Traffic 8, 1035-1051.
Starkuviene, V., Liebel, U., Simpson, J. C., Erfle, H., Poustka, A., Wiemann, S. and
Pepperkok, R. (2004). High-content screening microscopy identifies novel proteins
with a putative role in secretory membrane traffic. Genome Res. 14 10A, 1948-1956.
Stepanenko, O. V., Stepanenko, O. V., Shcherbakova, D. M., Kuznetsova, I. M.,
Turoverov, K. K. and Verkhusha, V. V. (2011). Modern fluorescent proteins: from
chromophore formation to novel intracellular applications. Biotechniques 51, 313314, , 316, 318 passim.
Stephens, D. J. (2003). De novo formation, fusion and fission of mammalian COPIIcoated endoplasmic reticulum exit sites. EMBO Rep. 4, 210-217.
Stephens, D. J., Lin-Marq, N., Pagano, A., Pepperkok, R. and Paccaud, J. P. (2000).
COPI-coated ER-to-Golgi transport complexes segregate from COPII in close
proximity to ER exit sites. J. Cell Sci. 113, 2177-2185.
Storrie, B., White, J., Röttger, S., Stelzer, E. H., Suganuma, T. and Nilsson,
T. (1998). Recycling of golgi-resident glycosyltransferases through the ER reveals a
novel pathway and provides an explanation for nocodazole-induced Golgi scattering.
J. Cell Biol. 143, 1505-1521.
Subramanian, D., Laketa, V., Müller, R., Tischer, C., Zarbakhsh, S., Pepperkok,
R. and Schultz, C. (2010). Activation of membrane-permeant caged PtdIns(3)P
induces endosomal fusion in cells. Nat. Chem. Biol. 6, 324-326.
Szul, T. and Sztul, E. (2011). COPII and COPI traffic at the ER-Golgi interface.
Physiology (Bethesda) 26, 348-364.
Tängemo, C., Ronchi, P., Colombelli, J., Haselmann, U., Simpson, J. C., Antony, C.,
Stelzer, E. H., Pepperkok, R. and Reynaud, E. G. (2011). A novel laser
nanosurgery approach supports de novo Golgi biogenesis in mammalian cells. J. Cell
Sci. 124, 978-987.
Toomre, D. and Bewersdorf, J. (2010). A new wave of cellular imaging. Annu. Rev.
Cell Dev. Biol. 26, 285-314.
Trucco, A., Polishchuk, R. S., Martella, O., Di Pentima, A., Fusella, A., Di
Giandomenico, D., San Pietro, E., Beznoussenko, G. V., Polishchuk, E. V.,
Baldassarre, M. et al. (2004). Secretory traffic triggers the formation of tubular
continuities across Golgi sub-compartments. Nat. Cell Biol. 6, 1071-1081.
Tsukada, Y. and Hashimoto, K. (2013). Feedback regulation of microscopes by image
processing. Dev. Growth Differ. 55, 550-562.
Verissimo, F. and Pepperkok, R. (2008). ER-to-Golgi transport. In The Golgi
Apparatus (ed. A. Mironov and M. Pavelka), pp. 333-341. Vienna: Springer.
Ward, T. H., Polishchuk, R. S., Caplan, S., Hirschberg, K. and LippincottSchwartz, J. (2001). Maintenance of Golgi structure and function depends on the
integrity of ER export. J. Cell Biol. 155, 557-570.
Wendler, F., Gillingham, A. K., Sinka, R., Rosa-Ferreira, C., Gordon, D. E.,
Franch-Marro, X., Peden, A. A., Vincent, J. P. and Munro, S. (2010). A genomewide RNA interference screen identifies two novel components of the metazoan
secretory pathway. EMBO J. 29, 304-314.
Westphal, V., Rizzoli, S. O., Lauterbach, M. A., Kamin, D., Jahn, R. and Hell, S. W.
(2008). Video-rate far-field optical nanoscopy dissects synaptic vesicle movement.
Science 320, 246-249.
Willig, K. I., Kellner, R. R., Medda, R., Hein, B., Jakobs, S. and Hell, S. W. (2006).
Nanoscale resolution in GFP-based microscopy. Nat. Methods 3, 721-723.
Xu, K., Babcock, H. P. and Zhuang, X. (2012). Dual-objective STORM reveals threedimensional filament organization in the actin cytoskeleton. Nat. Methods 9, 185-188.
York, A. G., Ghitani, A., Vaziri, A., Davidson, M. W. and Shroff, H. (2011).
Confined activation and subdiffractive localization enables whole-cell PALM with
genetically expressed probes. Nat. Methods 8, 327-333.
Zanetti, G., Pahuja, K. B., Studer, S., Shim, S. and Schekman, R. (2012). COPII and
the regulation of protein sorting in mammals. Nat. Cell Biol. 14, 20-28.
Zeug, A., Woehler, A., Neher, E. and Ponimaskin, E. G. (2012). Quantitative intensitybased FRET approaches—a comparative snapshot. Biophys. J. 103, 1821-1827.
Zeuschner, D., Geerts, W. J., van Donselaar, E., Humbel, B. M., Slot, J. W., Koster, A.
J. and Klumperman, J. (2006). Immuno-electron tomography of ER exit sites reveals
the existence of free COPII-coated transport carriers. Nat. Cell Biol. 8, 377-383.