suhel dahiwal

Suhel Dahiwal 902933653 Essay II MEDSCI 703

1

Visualizing Cell Architecture and Molecular Location Using Soft

X-Ray Tomography and Correlated Cryo-Light Microscopy


2

INTRODUCTION

The visualization and location of higher order cells is necessary to understand the

environmental and/or genetic factors affecting cell phenotypes. This essay includes two

correlated cellular imaging techniques CLM (Cryo-Light Microscopy) and SXT (Soft X-ray

Tomography), which are used to provide location of specific reacting molecules and a high-

definition visual description of sub cellular architecture respectively. These two imaging

techniques are carried out serially on the same sample of cells and the data obtained from two

modalities are merged to form a composite view that is significantly greater than the sum of its

component parts. Further, this data is segmented as per the cell needs to be viewed and finally,

this essay will discuss advantages, few applications and futures scope for this correlated

imaging modalities.

CELL ARCHITECTURE

Cell biology is responsible for various chemical reactions and interconnected molecular

interactions. Cells not only carry out specific chemical reactions but also perform them in vast

numbers. Each cell performs thousands, or even millions, of chemical reactions per second.

These cells are structured to create a range of microenvironments which supports cell

functions. (McDermott et al., 2012) Cell size and sub-cellular volume (organelle) are most

important physical characteristics for chemical and molecular reactions to occur. (Uchida et al.,

2011) Cells, particularly eukaryotic cells, are higher order cells and have verycomplex

structures. (Fig. 1) However, partition of eukaryotic cells into membrane-bound, sub-cellular

volumes termed as organelles radically changes reaction kinetics. (McDermott et al., 2012)


3

Fig. 1: Complex structure of higher order eukaryotic cell (Siegel, 2008)

HISTORY

Imaging modalities are primarily classified by the physical characteristics of their specimen

illumination. However, specimen illumination dictates factors such as maximum spatial

resolution and size range of specimens that can be imaged. (McDermott et al., 2012) The

imaging modalities used for imaging cell architecture is (conventional) fluorescence microscopy

and electron microscopy. However, both the modalities have their own limitations associated

with the imaging of cell biology. McDermott et al. (2012) stated that “fluorescence microscopy

is a very sensitive technique”and used to measure concentration of molecules along with the

relative molecular location. However, imaging of cells with the fluorescence microscopy is

limited up to 3µm. Electron microscopy is an imaging modality which is used to image very

small cells up to 700 nm on high resolution. (McDermott et al., 2012) However, due to low SNR

(signal to noise ratio), it is very difficult to segment the molecules after the image acquisition.

(Uchida et al., 2011)


4

CLM (CRYO-LIGHT MICROSCOPY)

CLM is a powerful tool for localizing molecules in a cell. The conventional fluorescence

microscopy has a limitation of photo bleaching (excess exposure of light to fluorescent tags

damages the image quality and life of fluorescent molecules). However, In CLM, the specimen is

cooled at cryogenic temperature (below -160⁰c) with the use of cryogens such as liquid

propane as an immersion fluid. The low-temperature microscopes used in the past are

operated in air with the low numerical aperture lenses causing mismatch of refractive index,

degradation of maximum spatial resolution and fidelity of an image. (Smith et al., 2014)

However, CLM uses cryogenic immersion lens which allows frozen specimen to be imaged at

high spatial resolution by using index-matched cryogens. With the use of cryogen, cell

(specimen) is kept in its native state (original microenvironment) and hence causing constant

cumulative exposure to the cell. (Fig. 3) The frozen (amorphous ice) specimen is then labeled

using fluorescent tags such as green fluorescent protein. However, use of electron dense tag in

immune-labeling causes damage to the specimen. (McDermott et al., 2012) Fig.2 shows an

overview of CLM.

Fig.2: Overview of cryogenic fluorescent microscope (Cinquin et al., 2014)


5

Fig. 3: Photo bleaching curves for yellow fluorescent protein, (YFP), expressed in E. coli. (A) The

blue curve shows fluorescence decay at cryogenic temperature; the red curve shows decay at

room temperature. The resistance to photo-bleaching at 77 K is ∼50 times that observed at

room temperature; (B) low-temperature bleaching curve plotted over a longer time period.

(LeGross et al., 2009)


6

SXT (SOFT X-RAY TOMOGRAPHY)

Soft X-ray tomography is an imaging modality which is used in correlation with CLM to visualize

cell biology. SXT is a non-invasive method for imaging the internal structure of intact cells with

the use of grazing-incidence reflective optics to focus the X-rays on to specimen. (Kirkpatrick et

al., 1995) However, SXT uses Fresnel zone optical system situated into a third generation

synchrotron light source in a soft X-ray microscope. (Fig.4) (McDermott et al., 2012). SXT

produces soft X-rays of 0.28 Kev-0.53 Kev within a region called as “water window” (K-edge of

X-rays between oxygen-2.34nm and carbon-4.4nm) Soft X-rays are attenuated more strongly by

carbon and nitrogen relative to their attenuation by water. The absorption of X-rays adheres to

the Beer-Lambert law and is therefore a linear, quantitative and a function of thickness and

chemical composition of the specimen. (I.e. X-ray absorption will vary in accordance with the

thickness and concentration of the specimen)

Fig.4: The optical configuration of a bend magnet–based soft X-ray microscope. The specimen

sits between the objective and the condenser optical elements. (McDermott et al., 2012)

There are two main components of SXT; a) Synchrotron light source b) Fresnel zone plates


7

a) Synchrotron source

Synchrotron light source is the optimal source of illumination photons for a soft X-ray

microscope. (McDermott et al., 2012) These light sources produce intense beam of X-

rays that can be readily collimated and focused into tiny specimens. The synchrotron

light source has many advantages including high accuracy, zero errors from beam

hardening or scattering, high spatial resolution and production of photon with energy-

selective narrow bandwidth. (Adam et al., 2009) However, synchrotron light sources are not

readily available in the laboratory. (McDermott et al., 2012) Efforts are taken to increase the

productivity and produce tabletop X-ray sources which can be used in the laboratory.

(Tuohimaa et al., 2008)

b) Fresnel zone plates

Fresnel zone plate contains radically symmetric rings known as Fresnel zones. (Andersen

et al., 2000) In a soft X-ray microscope Fresnel zones alternate between being opaque

and transparent toward X-ray photons. In operation, a soft X-ray beam diffracts around

the opaque zones (McDermott et al., 2012). The zones can be spaced so that the light

diffracted by each zone constructively interferes at the desired focus. Zones become

narrower and more closely packed towards the outer side of zone plate from the centre,

until the outermost zone is reached. The spatial resolution of SXT depends upon the

outermost zone of objective zone plate. (McDermott et al., 2012)

Fig. 5: Overview of Fresnel zone plate (Source: ESCO)


8

The focal length (f) of a zone plate is,

f=OD ∆Rn /λ …………… (1)

Where,

OD = Diameter of zone plate

∆Rn = Outermost zone width

λ = X-ray wavelength

Fig.6: Scanning mechanism of the CLM-STXM as seen from the direction of the incident X-ray

beam. The cryo specimen holder is inserted into the vacuum chamber through an airlock, which

inturn is connected to the vacuum chamber through bellows. A precision lever mechanism

allows horizontal and vertical motion ofairlock and specimen holder. The tip of the cryo holder

is placed in a receptacle on the scanning stage, and held in place by anadjustable preload. For

high resolution scans, an in-vacuum flexurestage moves the specimen holder horizontally and

vertically.Coarse scans are performed by moving the whole fine stage and the specimen holder

using out-of-vacuum linear stages driven bystepping motors. (Maser et al., 2000)


9

SPECIMEN PREPARATION

The specimen preparation for CLM-SXT is very minimal. Specimen preparation is an important

factor in determining the final quality and fidelity of any biological imaging

technique.(McDermott et al., 2012) Specimen is filled in a cylindrical holder usually a glass

capillary. However, use of flat surface (glass slide) for the specimen preparation increases the

specimen thickness through rotating axis while collecting the data. (Fig.7) (Cinquin et al., 2014)

However, glass capillary should be sized to match the cells being imaged since excess solution

surrounding cells adds background noise to the image. (McDermott et al., 2012)

Before loading the specimen, the glass capillary is dipped in poly-L-Lysine (0.01% Tissue culture

Grade) and immediately dipped in a solution of 100 nm gold nano-particles such as EMGC 100,

which are used as fiducial markers to align x-ray projections.(Smith et al., 2014). The glass

capillary is then heated and is then pulled to form an extended narrow tip. (McDermott et al.,

2012) The specimen is filled into a glass capillary using standard micropipette and treated with

cryogenic temperature (below -160⁰c). The frozen specimen is then cryo-transferred into

custom boxes using a home-built cryo-transfer device and stored in liquid nitrogen. (Smith et

al., 2014)

3D IMAGING

3D imaging is an important tool to visualize the internal structure of the specimen. The 2D

images captured by an imaging modality have internal structures superimposed on top of each

other causing difficulty in understanding the cell biology. However, if 2D images are captured

using different angles (over 360⁰c) around the rotation axis, a 3D tomographic reconstruction

can be calculated. (Fig.7-A) (McDermott et al., 2012) this process is done well within the

threshold of cumulative exposure required to cause observable radiation damage. (Fig.3) the

process of converting 2D projection images to 3D images is called “tomogram”.

The SXT is developed with the readily available sophisticated software packages (such as

AMIRA) for data processing and analysis. However, there are algorithms such as back-projection


10

and algebraic reconstruction technique (ART) available for reconstruction of three-dimensional

volumes from two-dimensional soft X-ray projection series. (Marabini et al., 1998)

Fig. 7: Difference between (Cylindrical holder) glass capillary and (Flat surface) glass slide for

imaging isotropic data A) 3D imaging of the specimen by collecting data from rotation of

cylindrical holder by 360⁰c B) Rotation of the specimen using glass slide C) Difference in the

thickness value 5µm, 7.1µm, 16µm by rotation of 0⁰, 45⁰, 72⁰ respectively. D) Graph showing

the curve of thickness (in µm) which changes with angles (in degrees) (Cinquin et al., 2014)


11

ALLIGNMENT

The alignment of CLM-SXT is very important to image the specimen with high spatial resolution.

The alignment is done using fiducial markers. (Fig. 8) The fiducial markers are used in both

ways; externally (onto the glass capillary) with the help of poly-L-Lysine, 100 nm gold

nanoparticles and internally with the help of red polystyrene microspheres (Fluro-Spheres

Carboxyl ate-Modified Microspheres, 0.2 mm, dark Red Fluorescent (660 excitation/ 680

emission), which served as fluorescence fiducials. (Smith et al., 2014) However, fiducial markers

are applied to specimen internally by fluorescently labeled organelles such as liquid droplets,

nucleus and granules. (Cinquin et al., 2014)The most common software used for alignment is

AMIRA. (Smith et al., 2014)

The alignment is done through z-stacks (data obtained by displacing glass capillary in z-axis)

using fluorescent fiducial markers. The fiducial co-ordinates are used to write as a new image

stack containing a spherically representation of fiducials which is termed as fiducial model.

Thehighest intensity values in the fiducial model correspond to the positionof the center,

surrounding voxel’s intensity values fall off as the distance from the center is increased. The

voxel dimensions of the fiducial modelswere first sampled to match the preprocessed data set

and then reduced stepwise until the errors inaligning the data sets plateaued (measured by the

distances between fiducial centers). (Smith et al., 2014)


12

Fig. 8: Allignment of CLM-SXT imaging data using fiducial markers (Cinquin et al., 2014)

SEGMENTATION

Segmentation is the process of computationally isolating, visualizing and quantifying the

specific cellular components in a tomography reconstruction. In CLM-SXT, quantification is done

by segmentation of boundary regions using LAC (Linear Absorption Coefficient). LAC represents

the absorption values for each voxel in the reconstruction. Biological material attenuate soft X-

ray photons according to Beer’s law, the LAC values for identical sized voxels depends solely on

the concentration and composition of biomolecules present, with water having an order of

magnitude lower (Lower LAC) than molecules such as lipids and proteins. (Smith et al., 2014)


13

Fig. 9: Detailed analysis of LAC values of X chromosome segmented from correlated CLM-SXT

reconstruction of female v-able macroH2A-EGFP transformed thymic lymphoma cells.

Representation of soft x-ray LAC values for X chromosome segmented from the SXT

reconstruction, shown from two perspectives 180⁰ apart. LAC values are categorized as high

(0.34–0.36 µm-1), medium (0.32–0.34 µm-1), or low (0.30–0.32 µm-1). From left to right the

pairs show combinations of the high, medium, and low LAC values measured in the

reconstruction. LAC color code: high, dark blue; medium, light blue; low, gold. Right-most

segmentations show all LAC values combined, together with a section of NE that makes contact

with the reconstruction (indicated by dashed ovals). (Smith et al., 2014)

Each organelle (sub-cellular volume) has a characteristic average LAC value depending upon

their chemical composition and thickness. Highly dense biomolecules such as lipid bodies,

nucleus has high LAC than the less dense molecules like vacuoles. (Fig. 10) (McDermott et al.,

2012) However, these characteristic values not only hold between cell of same type, but also

frequently are seen to hold between the cells from different species. (Uchida et al., 2011)


14

Fig.10: Segmentation of organelles based on linear absorption coefficient (LAC) values in

Saccharomyces cerevisiae cell of yeast. (A) A representative diploid cell shown in an ortho-slice

(i.e. a single slice of tomographic data) and individually segmented organelles; scale bar = 1 μm.

(B) LAC values for each organelles. (C) Five different vacuolar compositions found in

tomographic data [left; the similar sizes of vacuoles were selected (i.e., 1 μm)], schematic views

(middle) and LAC values (right; indicates LAC values of structures inside vacuoles) (Uchida et al.,

2011)

Figure 10 represents the segmentation of organelles based on linear absorption coefficient

(LAC) values in yeast. Once the projection images were reconstructed, the volumes were

segmented to isolate individual cells and subsequently their component organelles (Figure

10A). The reconstructed cells were segmented into discrete volumes based on the LACs (Figure


15

10B). For instance, volumes assigned as dense lipid bodies have an average LAC value of 0.55

μm-1compared with more transmissive organelles, such as nuclei, nucleoli, vacuoles and

mitochondria that have typical LAC values of 0.26, 0.33, 0.22 and 0.36 μm-1, respectively.

Assignment of organelle type to a particular segmented volume is guided by morphological

characteristics established by CLM imaging modality. For example, the nuclei/nucleoli,

mitochondria and vacuoles have distinct and very recognizable morphologies. Once vacuoles

from a number of cells had been segmented, it is categorized into five types, based on their

morphology, internal structure and densities. The LAC values for these are shown in Figure 10C.

ADVANTAGES

1) CLM-SXT produces excellent contrast without the use of contrast-enhancing stains e.g.

metals such as osmium, platinum

2) CLM-SXT increases the life of fluorescent molecules

3) CLM-SXT resolves ambiguities such as same size and same LAC (Linear Attenuation

Coefficient) over segmented regions in reconstruction

4) CLM-SXT produces impressive throughput of samples as the specimen preparation is

very minimal

5) CLM-SXT measures the volume of cell along with the high spatial resolution (up to

10nm) (Chao et al., 2005)

APPLICATION

The CLM-SXT correlated imaging modality has various applications. Due to its excellent

contrast, the CLM-SXT is used to visualize sub-cellular architecture of eukaryotic cells such as

yeast (Fig.11). (McDermott et al., 2012)The CLM-SXT is used in imaging of thymic lymphoma

cells. (Fig.12) (Smith et al., 2014) The CLM-SXT is not only used in imaging malaria parasite such

as plasmodium falciparum but also used to image mouse adenocarcinoma cells. (Cinquin et al.,

2014 and Schneider et al., 2010)


16

Fig.11. Correlated soft X-ray tomography and cryo-light imaging (wide-field fluorescence). (a)

The vacuoles fluorescently labelled and imaged by cryo-light microscopy. (b, c) Slices through

the volumetric reconstruction calculated from soft X-ray tomography data, with the vacuoles

shown as segmented volumes in panel c. The segmented vacuoles correlate closely with the

locations determined from cryo-light microscopy. (d) The same cell after the major organelles

have been segmented. The nucleus is shown in blue, the nucleoli in orange, mitochondria in

grey, vacuoles in light grey, and lipid droplets in green. Scale bar = 1 μm. (McDermott et al.,

2012)


17

Fig.12. Correlated CFT-SXT imaging of female v-able macroH2A-EGFP transformed thymic

lymphoma cells. (A) Four virtual sections from the de-convolved CFT reconstruction. (B) The

corresponding virtual sections from the SXT reconstruction. White arrow shows the closest

contact between Xi and the nucleolus. (C) The same sections in the combined CFT-SXT

reconstruction. (D) A 2-D projection of the Xi CFT reconstruction. (E) Cutaway of a volume

rendered SXT reconstruction. The surface of the cell is coloured light blue. LAC values are

represented in grey scale, ranging from high (dark) to low (light). (F) The CFT reconstruction

shown in (D) overlaid into the volume rendered SXT reconstruction shown in (E). (G) Surface

rendering of the inactive X chromosome segmented from the SXT reconstruction after

identification by macroH2A-EGFP CFT. The deep blue shaded areas are regions of high LAC that

contact the nuclear envelope. (Smith et al., 2014)


18

FUTURE SCOPE

CLM-SXT with the Fresnel zone plate has many advantages including imaging of higher order

cells without using contrast-enhancing stains. However, ultra high resolution zone plate and

table-top synchrotron X-ray sources will allow cells to be imaged with a significantly greater

level of detail in the future. (McDermott et al, 2012 and Cinquin et al, 2014)

CONCLUSION

The correlated CLM-SXT imaging modality is an emerging modality for visualizing high-definition

sub-cellular architecture and locating specific bio-molecules. Excellent contrast, extended life of

fluorescent molecules, minimal specimen preparation, impressive throughput of samples,

solution of ambiguities (same size and same LAC) over segmented regions make CLM-SXT more

suitable for drug discovery, biomedical research and basic cell biology. However, further

improvements need to be done to increase the spatial resolution.


19

REFERENCES

1. Adam, J., Bayat, S., Porra, L., Elleaume, H., Estève, F., &Suortti, P. (2009). Quantitative

functional imaging and kinetic studies with high‐z contrast agents using synchrotron

radiation computed tomography. Clinical and Experimental Pharmacology and Physiology,

36(1), 95-106.

2. Chao, W., Harteneck, B. D., Liddle, J. A., Anderson, E. H., & Attwood, D. T. (2005). Soft X-ray

microscopy at a spatial resolution better than 15 nm. Nature, 435(7046), 1210-1213.

3. Cinquin, B. P., Do, M., McDermott, G., Walters, A. D., Myllys, M., Smith, E. A., & Larabell, C.

A. (2014). Putting molecules in their place. Journal of cellular biochemistry, 115(2), 209-216.

4. http://www.esco.co.kr/v3/product/p_content_d.php?mt=2&dt=8&st=145

5. Le Gros, M. A., McDermott, G., Uchida, M., Knoechel, C. G., & Larabell, C. A. (2009).

High‐aperture cryogenic light microscopy. Journal of microscopy, 235(1), 1-8.

6. Marabini, R., Herman, G. T., & Carazo, J. M. (1998). 3D reconstruction in electron

microscopy using ART with smooth spherically symmetric volume elements

(blobs). Ultramicroscopy, 72(1), 53-65.

7. McDermott, G., Fox, D. M., Epperly, L., Wetzler, M., Barron, A. E., Le Gros, M. A., & Larabell,

C. A. (2012). Visualizing and quantifying cell phenotype using soft X‐ray

tomography. Bioessays, 34(4), 320-327.

8. McDermott, G., Le Gros, M. A., & Larabell, C. A. (2012). Visualizing cell architecture and

molecular location using soft x-ray tomography and correlated cryo-light microscopy. Annual

review of physical chemistry, 63, 225.

9. Schneider, G., Guttmann, P., Heim, S., Rehbein, S., Mueller, F., Nagashima, K., ... & McNally,

J. G. (2010). Three-dimensional cellular ultrastructure resolved by X-ray microscopy. Nature

Methods, 7(12), 985-987.

10. Smith, E. A., McDermott, G., Do, M., Leung, K., Panning, B., Le Gros, M. A., & Larabell, C. A.

(2014). Quantitatively Imaging Chromosomes by Correlated Cryo-Fluorescence and Soft X-

Ray Tomographies. Biophysical journal, 107(8), 1988-1996.

http://www.esco.co.kr/v3/product/p_content_d.php?mt=2&dt=8&st=145


20

11. Tuohimaa, T., Ewald, J., Schlie, M., Fernandez-Varea, J. M., Hertz, H. M., & Vogt, U. (2008). A

microfocus x-ray source based on a nonmetal liquid-jet anode. Applied Physics

Letters, 92(23), 233509-233509.

12. Uchida, M., Sun, Y., McDermott, G., Knoechel, C., Le Gros, M. A., Parkinson, D., Larabell, C.

A. (2011). Quantitative Analysis of Yeast Internal Architecture using Soft X-ray

Tomography. Yeast (Chichester, England), 28(3), 227–236. doi:10.1002/yea.1834

suhel dahiwal

Documents