Optical whereas LSCM’s use scanning mirrors to mobilise the

Optical microscopes are used for
visualisation and imaging of biological specimens. When compiled with the wide
variety of image processing programs available, allow the quantification of
numerous features of a specimen to be examined. The development of epifluorescence
microscopy extended this field, allowing specific aspects of the cell to be
further analysed. This includes dynamics, interactions and cellular
localisation of proteins and other macromolecules such as genetic material.
Moreover, within this expanding field of microscopy, more and more techniques
are being developed which grant scientists to gauge the magnitude of
fluorescence to observe cellular changes oblivious to the human eye. Such
techniques include photo-activation using pulses of UV light (Patterson, 2011), fluorescence recovery after
photobleaching (FRAP) (Hagen et al., 2009), and fluorescence resonance
energy transfer (FRET) (Lee, Wee, & Brown, 2014; Sekar & Periasamy,
2003)

As with all forms of microscopy, epifluorescence microscopy has
its limits. This includes photo-bleaching, photo-toxicity and resolution (Combs, 2010). Resolution is defined as the
minimum distance between two features of a specimen which allows them to be
distinguished as independent objects (Lodish et al., 2000). Two key resolution
limitations exist. Firstly, the lateral spatial resolution, which is dictated
by the wavelength of light and the size of the objective lens numerical
aperture (Thorn, 2016). Secondly, resolution is also
limited by the optical (z) axis. This is because high resolution detail can
only be observed near the focal plane. This opposes low resolution detail which
can only be observed further from the focal plane (Fouquet et al., 2015).

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Focussing the microscope on a specific focal plane, however,
mediates the illumination of all areas surrounding that focal plane, and the
unification of light along the z axis. This produces a blurring effect. Therefore,
the in-focus light may be over-whelmed by the out-of-focus blur (McNally, Karpova, Cooper, & Conchello, 1999). To overcome this issue, the
out-of-focus light must be excluded. Two methods which utilise this feature
will be discussed here, deconvolution microscopy and confocal microscopy.

The basic anatomy of a fluorescence microscope is shown
below in figure 1. Deconvolution microscopy (DM) and laser scanning confocal
microscopy (LSCM) possess differences. Firstly, LSCM’s use a laser opposed to a
lamp which is used in DM. Secondly, DM requires a diffuser to illuminate the
whole specimen at once; whereas LSCM’s use scanning mirrors to mobilise the
laser across the sample to obtain an image point by point (Combs, 2010). Thirdly, the method of
detection differs. For DM a CCD camera is employed whereas a photomultimer tube
is commonly used for LSCM (Swedlow & Platani, 2002).

Moreover, these two microscopy techniques utilise different
methods to eliminate out-of-focus light. LSCM’s exploit the use of a pinhole.
This lies in conjugate with the image plane and filters out the out-of-focus
light whilst targeting the in-focus light to the point detector. This contrasts
DM. A detailed knowledge of the microscopes point spread function (PSF) is required,
based on objective lens properties and the conditions the images are acquired. The
specific light wavelength and its diffraction pattern produced by the lens
system blur any single point of light, this effect is known as the PSF. DM
entails the reversal of this effect, it uses an iterative restoration algorithm
based on the equation image = object  Ä PSF to reinstate this
blur to its original focussed location creating a clearer image (Alberts et al., 2002).

Materials and Methods

HeLa cells placed on glass coverslips suitable for
wide-field and confocal microscopy. Cells fixed and stained with
Anti-tubulin-Alexa 546, Phalloidin-Alexa 488 and DAPI. For confocal microscopy,
a Zeiss LSM880 microscope was used to obtain 3D data set by capturing
sequential images at a range of focal depths. For deconvolution microscopy, a
DeltaVision Widefield Deconvolution system was employed to collect a z-stack of
images. A deconvolution algorithm was utilized iteratively to restore
out-of-focus light signal and distortion created whilst imaging. Analysis using
ImageJ (FIJI) was then conducted on both data sets. Analysis includes
adjustment of brightness/contrast, colour optimisation, RGB image formation,
scale bar addition and threshold adjustment.

Results and Discussion

The diffraction of light along the z-axis, required for
magnification of sub-resolution objects, leads to the incorporation of
out-of-focus light from each image plane being incorporated into the final
image. The resultant blur dramatically reduces the contrast and signal: noise
(S:N) ratio of the image. Reduced S:N ratio jeopardises resolution which
impedes the distinguishability of sub-cellular features. Deconvolution of the
data reverses this process and improves these features by reassigning the
blurred light (Swedlow, Sedat, & Agard, 1993; Wallace, Schaefer,
& Swedlow, 2001). This can be seen in the figure 2 below. Here we
see two images of a HeLa cell during metaphase. The image on the left is a
widefield fluorescent image whilst the image on the right is the same image
with an applied deconvolution algorithm. The deconvolved image has increased
contrast allowing the increased visualisation of the mitotic spindle fibres
which are much more difficult to observe in the widefield fluorescence image. Moreover,
with improved S:N ratio the individual phalloidin fibres within the cell are
more distinct and observable.

LSCM utilises a pinhole to eliminate out-of-focus light
leading to superior axial resolution. This has the advantage of increasing the
preciseness of focal sectioning and enhancing contrast (Shaw, 2006). An example of superior
lateral resolution can be seen in figure 3 by comparison of the deconvolved
(figure 3B) and laser scanning confocal image (figure 3D) of a HeLa cell during
metaphase. The spindle fibres are more clearly visible with greater
fluorescence in figure 3D, despite being overlaid by the DAPI stain.

However, this comes at a price as the detection sensitivity
is diminished leading to reduced lateral resolution, a problem especially when dealing
with small amounts of fluorescence (Le Puil et al., 2006). Moreover, scanning a
confocal laser across the sample pixel by pixel is a slow process and the high
intensity of the laser can lead to bleaching of dyes and phototoxicity of live
cells (Shaw, 2006). Despite this, the software
required for confocal microscopy allows the undertaking of 3D, 4D and even 5D
analysis as well as spectral deconvolution and other techniques including FRET
and FRAP. Furthermore, a variable pinhole size allows a range of optical section
thickness values to be exploited, a feature beneficial to thicker samples.
Additionally, the incorporation of a greater number of fluorophores allows more
features of a cell to be analysed at once (Combs, 2010).

As discussed previously, deconvolution microscopy is
advantageous as it reassigns out-of-focus light to improve S:N ratio and
contrast allowing sensitivity to even the lowest of signals. This can be
observed in figure 3 below where Phalloidin fibres are more distinct and
separated due to the higher level of lateral resolution. Deconvolution
microscopy, however, is not suitable for thick specimens, the overall process
is much more memory intensive and much longer due to the extensive iteration
process required for image regeneration (Shaw, 2006). Also, artefacts may become
introduced during the process. The development of increasingly powerful
computers and decreased cost have lead to rapid improvements in this form of
microscopy (Markham & Conchello, 2002).

Cell mitosis is divided up into 4 stages, with a 5th
stage, known as Interphase, accounting for cell growth and DNA replication
needed for mitosis. Interphase is characterised by decondensed chromosomes
which are evenly dispersed throughout the nucleus giving it a uniform
appearance. This can be seen in figure 4A. Cells during this stage also
increase in size due to the high level of cell growth and DNA replication (Li, Sudlow, & Belmont, 1998). The first stage of mitosis,
known as Prophase is outlined by the condensation of chromosomes and the migration
of centrosomes to opposite cellular poles to form the mitotic spindle, as well
as the breakdown of the nuclear envelope (Georgi, Stukenberg, & Kirschner, 2002). These features are clearly
shown in figure 4B.

The second stage, namely Metaphase, describes the third
stage of mitosis. Here spindle fibres align the condensed chromosomes at the
metaphase plate at the centre of the spindle (Guo, Kim, & Mao, 2013). This is shown in figure 4C.
Figures 4G and 4H further elucidate this mechanism. Anaphase is the third stage
of cell mitosis. Events which occur during this stage include the contraction
of mitotic spindle leading to separation of sister chromatids, and their
subsequent migration to the spindle poles (Asbury, 2017). Figure 4D reveals this migratory
event. The final stage of mitosis is named Telophase. Here, reformation of the
nuclear envelope occurs around the nuclei of the two daughter cells as the
chromosomes decondense. This is followed by cytokinesis. Evidence for this is
revealed in figure 4E as the midbody, a characteristic final connection between
the two daughter cells of Telophase is identifiable, as well as two sets of
decondensed chromosomes surrounded by nuclear envelopes (Walczak, Cai, & Khodjakov, 2010).

The area and perimeter of cells in each stage of mitosis
were measured and results presented in figure 5 below. Cytokinesis during late
anaphase/early telophase, leading to the production of 2 independent daughter
cells, accounts for cells in this stage possessing the largest area and
perimeter measurements. Prophase possesses a larger area than interphase as
throughout interphase, cell growth and DNA replication increase the cells size
in preparation for cell division (Cooper, 2000). A decline in constitutive
recycling of membranes during Prophase and Metaphase, whilst endocytosis
remains perpetual, leads to a noticeable decrease in area and perimeter
measurements during these stages. Once Metaphase is complete, recycling of
membranes commences again leading to an increase in area and perimeter during
anaphase and subsequent telophase (Boucrot & Kirchhausen, 2008). Area measurement is a
positive contribution to our qualitative results as it allows changes in cell
size to be monitored aiding in allocation of imaged cells to a specific cell
cycle stage.

In conclusion, deconvolution microscopy and confocal
microscopy are very useful tools for improving image resolution. Whilst LSCM is
more beneficial for improvements in axial resolution, DM is more favourable for
improvements in lateral resolution. Both forms of microscopy, however, allowed
the identification and allocation of cells to a specific cell cycle stage
depending on stained sub-cellular components. Moreover, the use of area and
perimeter measurements further reinforced cell cycle stage allocation due to cell
size changes during mitosis.