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Exploration of Optical Topometry to Study the Epidermal Surface of Arabidopsis thaliana
Distinction Paper for Molecular and Cellular Biology
Ryan David Kelsch Senior, Molecular and Cellular Biology
University of Illinois at Urbana-‐Champaign
Research Advisor: Dr. Thomas Jacobs Ph.D Department of Plant Biology
University of Illinois at Urbana-‐Champaign
March 27, 2013
Abstract
The development of the epidermal surface in Arabidopsis thaliana is affected
directly by environmental factors including those associated with climate change.
Current methods for studying the surfaces of plants are tedious with evolving
technology. Researchers studying epidermal development in plants are concerned
with several functionally and structurally different cell types, whose development
are governed by both environmental and genetic factors. A high throughput method
to study the epidermal surface of plants that provides precise quantitative
measurements for quantitative genetic analysis is therefore necessary. Optical
topometry (OT, a subset of optical profilometry) is a technology used to map a
micro-‐scale surface in three dimensions and at nanometer precision. Such data sets
can be mined by specialized software to perform analyses which can reveal
biologically relevant features of a plant’s epidermal topography mediated by the
three-‐dimensional patterning of cells. My research used OT to reinvent known
parameters and to discover novel parameters to describe the epidermal surface. In
addition, wild type plants were compared to a reported epidermal cell mutant. Also
in addition, developmental studies compared tissues within a single plant and also
between plants at different developmental stages. Through these experiments, I was
able to evaluate new parameters such as three-‐dimensional surface area, which
gives a quantitative snapshot of the overall topography. Established parameters
were also measured, such as the tallying of key epidermal cells, as this is key to
quantifying plant developmental responses to climate change. OT was able to obtain
conclusive results in a high-‐throughput fashion with no tissue preparation time and
yielded three-‐dimensional data sets indicative of the topographical features of the
epidermis at the nanometer scale. This research has served as a proof-‐of-‐principle
for creating a new standard for plant epidermal methodologies using optical
topography, and has also opened doors for using optical topography to study any
biological surface.
Introduction
Current methods for studying the epidermal surface of Arabidopsis thaliana
(a model organism of plant biology) are tedious, especially in the face of evolving
technology. Researchers in plant biology are concerned with the numbers of both
pavement cells and stomata per unit area of the epidermis. Stomata are pairs of cells
that are pair-‐of-‐lips like in morphology and are involved in gas exchange (CO2 in and
H2O out). Pavement cells form a jigsaw puzzle-‐like pattern over the majority of the
epidermal surface area. The numbers from counting of these two cell types can be
used to determine stomatal densities (the number of stomata per given area) and
stomatal indices (Equation 1), which are established quantitative representations
used for phenotyping and understanding underlying genetics. (Royer 2000). These
phenotypes are of developmental interest due to our atmosphere’s increasing CO2
concentration and the stomate’s key role in removing CO2 from the atmosphere
(IPCC, 2007). A high throughput method to study the epidermal surface of plants
that provides the precise quantitative measurements needed for genetics would be
of great service to the plant research community.
𝑆𝐼 % =𝑠𝑡𝑜𝑚𝑎𝑡𝑎𝑙 𝑑𝑒𝑛𝑠𝑖𝑡𝑦
𝑠𝑡𝑜𝑚𝑎𝑡𝑎𝑙 𝑑𝑒𝑛𝑠𝑖𝑡𝑦 − 𝑒𝑝𝑖𝑑𝑒𝑟𝑚𝑎𝑙 𝑐𝑒𝑙𝑙 𝑑𝑒𝑛𝑠𝑖𝑡𝑦𝑋100
Equation 1. Stomatal Index Equation
The current method for generating images suitable for taking a census of
cells populating the plant epidermis is via nail polish impressions. These are viewed
under the microscope and cell counts are taken from recorded images. Image
quality from nail polish impressions is variable to such a degree that automated
counting via computer learning has not been possible. A more robust, higher
throughput method could permit faster counting and the possibility of employing
quantitative genetics and other numerically intensive methods to this all-‐important
interface between plants and the aerial environment.
Optical topometry (OT) is a technology used to collect a set of images,
layered in such a way to create a set of three-‐dimensional data points that together
describe the topographical features of a surface at potentially nanometer-‐level
precision. This mature technology finds intensive application in microelectronics
and materials science, but has yet to be applied in a systematic fashion to many
biological questions, particularly regarding plant surfaces. Data sets can be mined
by dedicated software to generate an array of analyses that can be performed on a
surface in three dimensions. A nail polish impression image, by contrast, tends to
have low resolution of cells and high variability of quality, presenting a data set
limited to the shading of pixels. OT generates functional data sets that can be
manipulated and analyzed to an extent limited only by the investigator’s
exploitation of existing, highly capable topographic analysis software (Figure 1).
Other advantages of OT over nail polish include dramatically decreased sample
preparation time (hours to seconds), the ability to take data directly on live tissue in
a repeated non-‐destructive fashion, and decreased variability between data sets so
that automated counting is feasible.
Figure 1. Optical Topometry and Nail Polish Comparison. Both images have the
same unit area of the same leaf. OT rendering depicts surface slopes and Z-‐
dimensional lobing, whereas this is absent from the largely 2D nail polish
impression A. Rendering of intensity layer of OT data set. B. Nail polish impression
image.
In this study, the instrument used to obtain data sets describing the
epidermal surface of A. thaliana was the NanoFocus μsurf Explorer. This instrument
uses spinning disc confocal microscopy to obtain topometry data sets. While
A B
capturing the three-‐dimensional data, the instrument also records an intensity
rendering of the surface based on surface reflectivity (Figure 1A).
Optical topometry offers a novel alternative to measuring important plant
phenotypes. Other methods, such as scanning electron microcopy, atomic force
microscopy (Mechaber, et al., 1996), dental resin impressions and nail polish
impressions, are either too costly or destructive to the epidermal surface (due to
preparation time or in the preparation used). Topographical techniques other than
OT are time consuming, inaccurate and sometimes alter the tissue in their sample
preparation (i.e. histological sectioning, other types of three-‐dimensional
microscopy) (Wutys, et al., 2010) (Truernit, et al., 2008). OT provides a solution that
is inexpensive (apart from the initial cost of the instrument and software) and
completely non-‐destructive to the epidermal surface. It may also provide novel,
measurable parameters that can be attained in a high throughput fashion. In order
to explore this technology, three studies were undertaken, each intended to evaluate
facets of OT as a viable approach to analyzing the epidermal surface of plants.
Studies on Rop2 Mutants
rop2 mutants of Arabidopsis thaliana display a decrease in interdigitation
(lobing) of leaf epidermal pavement cells (Fu, et al., 2005). A lobe is defined an
outgrowth from the cell center of a pavement cell, in the plane of a captured image
(Fu, et al., 2005). In the context of three-‐dimensional data sets, a lobe must be
redefined as an area of local maximum in the z dimension, perpendicular to the
plane of the leaf. This new definition also includes lobes of the cell center
“backbone” area, since local maxima can be observed there using OT, but not via
conventional microscopy as previously published (Fu, et al., 2005; Figure 2). rop2
acts in a pathway of microfilament formation that controls localized cell outgrowth
(Fu, et al., 2005). Epidermal cell outgrowth also occurs in the z-‐dimension (height),
as seen in coordinate slices (surface profile along a particular line traced on the
epidermal surface) of epidermal surfaces obtained by OT (Figure 2). A comparison
is made in this study between Col-‐0 (wt) and the rop 2 mutant as a proof of concept
(in such parameters as lobing) and to investigate new parameters (such as overall
surface area, lobing and lobe heights).
Figure 2. Coordinate slice of A. thaliana epidermal surface. A. Surface filtered to
remove 12 forms (removes any gradual trends), coordinates are marked on a
topometry diagram of where a slice is to be made. B. Coordinate slice of line
indicated in A, shows the varying heights along the “backbone” of the pavement cell
centered in the red box. The brackets indicate regions of local maxima that translate
into lobes in figure C. C. Resultant motif image of lobing pattern. The red box
encompasses the same physical location for the three images. D. Intensity image
containing the pavement cell of interest in the red box.
Studies Across an Entire Plant
Given that no published studies could be found that documented the
development of leaf cellular microtopography throughout the life of a plant, I
examined the entire leaf complement of several plants in an effort to identify trends
from young to old leaves and within a single leaf. As younger leaves tend to have
smaller pavement cells (Staff et al. 2012), it can be expected that leaves that are still
developing would have a greater three-‐dimensional surface area (due to a greater
number of cell-‐cell interfaces) and greater numbers of pavement cells per unit of
two-‐dimensional leaf area. With that in mind, parameters such as surface area, lobe
and pavement number, and isotropy were chosen to determine if trends could be
seen developmentally.
Studies on Leaf Six Developmentally
Leaf six of the wild type was chosen to look at developmentally, as it reaches
full maturity within a reasonable time and has enough surface to take multiple
measurements. The aim of this study was to determine if the three-‐dimensional
surface morphology of pavement cells -‐-‐ and that of the overall epidermal surface
they create -‐-‐ change as a leaf and the plant matures. It was predicted that an overall
decrease in pavement cells per two-‐dimensional area would be observed as leaves
matured, as younger leafs were seen in previous experiments (nail polish and SEM),
to have more, smaller pavement cells than more senior leaves (Staff et al. 2012). It
has also been shown that as pavement cells increase in size, interdigitation in the
plane of the leaf (lobing) also increases (Staff et al. 2012). Number of lobes out of the
plane of the leaf is predicted to also correlate to pavement cell size and number of
pavement cells given the same two-‐dimensional surface area.
Materials and Methods
Plant Growth
Seeds were imbibed and stratified in deionized (DI) water at 4˚C for 3-‐7 days
before planting. Seeds were planted in in 4 x 9 cell Compak™ trays in autoclaved soil
and vermiculite (LC1 Sunshine Professional growing mix and Strong-‐lite ® medium
vermiculite premium grade respectively), in a 3:1 ratio. For every 4L of soil mix, 2L
of water with 2 g of Gnatrol WDG ® was added to the planting mixture. The plants
were covered with a plastic dome until they reached approximately 10 mm in
diameter. Plants were thinned to one plant per cell of the tray and watered with
approximately 1 L of water per tray every week and after they reached about 20
mm, 0.5 grams of Gnatrol WDG ® and 0.75 g of Peter’s Fertilizer was added to the
weekly 1 L watering mixture. After approximately 1-‐2 months (Table 1, growth time
depends on particular experiment) of growth in 12 hr days (fluorescent light) at 20-‐
22° C, measurements were taken with OT and then nail polish impressions were
taken and catalogued (Table 1).
Accession/Mutant Number of
Plants Viewed
Days of Growth
Before Viewing
Leaf
(Leaves)
Viewed
Experiment
Rop2 2 27 1 Studies on Rop2
Mutants
Col0 3 49 6 Studies on Leaf Six
Developmentally
Col0 3 43 6 Studies on Leaf Six
Developmentally
Col0 3 32 6 Studies on Leaf Six
Developmentally
Col0 5 27 (leaf 1) 28 (leaf
6)
1 and 6 Studies on Rop2
Mutants and Studies on
Leaf Six
Developmentally
Col0 1 63-‐65 1 thru 40 Studies Across an Entire
Plant
Col0 1 71-‐72 1 thru 42 Studies Across an Entire
Plant
Col0 1 79-‐80 3 thru 50 Studies Across an Entire
Plant
Table 1. Growth time before data collection. Viewing refers to OT data collection
and then impression taking.
Data Collection
Data were collected for each of the studies using the NanoFocus μsurf
Explorer and via conventional nail polish impressions (using nail polish on the
abaxial surface, and then removal with tape). The abaxial surface of each leaf was
affixed to a glass microscope slide with double-‐sided tape. Data were collected
within 3 minutes after each leaf was removed from the plant. All data were collected
using the instrument’s 50x objective focused at a point midway between veins. For
the studies on rop2 mutants, data were taken at three points, proximal medial and
distal to the point of attachment of the leaf to the plant, on both sides of the central
vein. For the studies across an entire plant, data were taken between each vein,
between the tip and the distal-‐most vein and between the base and the basal-‐most
vein. For the leaf six developmental studies, data were taken at a medial position, on
both sides of the central vein. Every data set was measured with the same two-‐
dimensional area.
Data Processing
All data processing was performed using Nanofocus’s proprietary μsoft
Analysis Premium software package. This software tool includes a wide variety of
surface analysis algorithms of both industry-‐specific and more general purpose
natures. The software provides a variety of filters as well as offering the user the
option to make fine adjustments away from the system’s defaults. In order to enable
the software to identify individual pavement cells, cell-‐to-‐cell boundaries had to be
exaggerated. Twelve forms of the topometry surface were removed, eliminating the
gradual variation in height across the surface. For cell identification and counting, a
spatial filter was then applied that takes advantage of the height minima that occur
at cell-‐to-‐cell interfaces. The filter negatively amplified all minima below a
manually-‐set threshold, while the points directly adjacent to the minima were
positively amplifed to maxima (this is a so-‐called Mexican Hat filter). All points that
were not considered a minimum were then flattened so that the end result was
flattened pavement cell bodies surrounded by elevated cell wall interfaces
surrounding deep valleys between cells (Figure 3). A motif analysis was then
performed to detect pavement cells. Pavement cells were detected by asking the
program to search for local minima motifs that are at least 6% of the highest
maxima (to occlude the valleys between cells), and were at least 1% of the overall
surface area (to occlude stomata, other cell types, and artifacts) (Figure 4).
Although automated counting compared to manual counting does not always
produce the same results (automated counting tends to cut up larger pavement cells
into several motifs), automated means of counting remove any bias. If the identical
counting procedures are used to obtain all data sets, then differences should be
noted, regardless of differences between manual and automated counting in
methods for counting pavement cells.
Figure 3. Three-‐dimensional rendering of spatially filtered surface. Light
orange indicates a pavement cell body, dark orange the exaggerated maxima, and
yellow the exaggerated minima.
Figure 4. Motif analysis for pavement cell detection. Different colored segments
are computer counted pavement cells. Crosses are placed on minima of a motif.
Colors are overlaid on original 12-‐forms removed image.
Lobing requires the surface to be somewhat unaltered by the software to
obtain an accurate count of the number of lobes per unit area so that local maxima
are preserved. As in the case of searching for pavement cells, twelve forms were
removed from the surface. Defining a lobe as a local maximum in height (Figure 2), a
motif analysis was performed based on local maximal heights such that each motif
must be less than 0.1% of the overall surface area, the approximate size of a
pavement cell lobe (Figure 2C). The heights of these local maxima lobe motifs were
also recorded and averaged to produce an average lobe height.
Finally, μsoft Analysis Premium can calculate the three-‐dimensional surface
area of a surface in a given frame of view. It also can measure the overall isotropy of
a surface (directional independence, given as a percentage) and the first, second,
and third directions (prevailing orientation of objects) for any data set.
Statistical Analysis
For the studies on rop2 mutants, a t-‐test was used with a least similar
differences function with an alpha of 0.05. For the studies across an entire plant, an
ANOVA was used with covariance matrices because the data points were spatially
related. Each dependent variable covariance matrix was independently analyzed.
For the studies on leaf six developmentally, a t-‐test was used with a least similar
differences function with an alpha of 0.05 and a nested design.
Results
Studies on Rop2 Mutants
Optical topometry data sets for rop2 mutants (SALK line t-‐DNA insertion,
SALK_055328C) and Col-‐0 (wildtype) epidermis were collected from the first
matured leaf, on both sides of the central vein, and between bisecting veins
proximally, medially, and distally from the stem to the tip. The topometry portion of
each data set was analyzed using μSurf Analysis parameters. Lobe parameters were
determined from local maxima of the z-‐dimension (e.g. height), as well as a
maximum area of 0.1% of the surface area restriction. Motif analysis of lobe number
suggests a decrease in rop2 compared to Col-‐0, with decreased average height of
lobe motifs for the rop2 mutant (Figure 5BC). Motif analysis parameters of total
pavement cell numbers, after flattening of the surface and exaggerating cell-‐to-‐cell
interfaces, indicate no difference between Col-‐0 and rop2 (Figure 5A). Surface area
of the epidermis also displays an overall increase for the wt compared to rop2
(Figure 5D).
Figure 5. rop2 vs. wt epidermis. Analyses were performed on the entire data set of
a given area of the plant surface. A. Cell numbers were determined per unit area
after flattening and filtering the surface based on depression motifs that were at
least 6% of the highest peak and at least 1% of the overall surface area (p=0.4895).
B. Number of lobes per unit area were counted using height motifs generated using
an area of less than 0.1% of the total surface area (p=0.0285). C. Average lobe height
per unit area was measured from the center maxima of the lobe motif (p=0.0049) D.
Three dimensional surface area was measured across the unit area for each data set
(p=0.007).
Studies Across an Entire Plant
Optical topometry data sets were obtained of the epidermal surface of three
plants on every leaf that had not yet senesced, in every position between bisecting
veins, before the most proximal bisecting vein and after the last distal bisecting vein,
left of the central vein only.
Variable
Parameter Leaf Placement Leaf*Placement Pavement Cells 0.0001 0.0048 0.7041 Lobes 0.001 0.002 0.889 Lobe Height 0.3327 0.1034 0.9987 Surface Area 0.0001 0.0001 0.9873 Isotropy 0.41 0.7424 0.9732 First Direction 0.3135 0.2651 0.2715 Second Direction 0.3135 0.2651 0.3715 Third Direction 0.6742 0.0649 0.6649 Table 2. P values for studies across an entire plant.
Isotropy and its first, second and third directions were statistically
insignificant (Table 2), but their respective histograms show interesting groupings
at certain directions. It can be seen at the approximately 0°, 45°, 90°, and 135°
directions (Figure 6), that there are large groupings in the first, second and third
directions. In addition, isotropy has lower values, which indicates some
directionality in the features of the surface.
Figure 6. Isotropy and directions for entire plant. A. Histogram of isotropy, the x-‐
axis is percentage. B. Histogram of first direction, the x-‐axis is degrees (0-‐180°). C.
A
B
D
C
Histogram of second direction, the x-‐axis is degrees (0-‐180°). D. Histogram of third
direction, the x-‐axis is degrees (0-‐180°).
Surface area, lobe number and pavement cell number are all significant in
placement across a leaf (proximal to distal) and from leaf to leaf (Table 2). Lobe
height, while not significant at leaf or placement, is also grouped with these
parameters since its data follows a similar trend. 3D surface area, lobe height, lobe
number, and pavement cell number all follow the trend of having higher values in
young and old leaves and intermediate values in the leaves that are aged between,
creating an inverse bell curve (Figure 7). Lobe number and pavement cell number
follow the same trend across placement (proximal to distal), having inverse bell
curve shaped graphs, whereas 3D surface area and lobe height both have standard
bell curve shaped graphs.
Figure 7. 3D surface area, lobe height, lobe number, and pavement cell
number across leaves and placement of entire plants. Placement 1-‐7 on the x-‐
axis is proximal to distal. Placement number 7 had only one value and is considered
an outlier. Leaves are numbered 1-‐50 from oldest to youngest leaves. A. 3D surface
area across leaves (in µm²E2). B. 3D surface area across placement (in µm²E2). C.
Lobe height across leaves (µm E-‐2). D. Lobe height across placement (µm E-‐2). E.
Lobe number across leaves. F. Lobe number across placement. G. Pavement cell
number across leaves. H. Pavement cell number across placement.
Studies on Leaf Six Developmentally
Optical topography data sets were taken bilaterally of the central vein on wt
Col-‐0 plants at a position midway between the central vein and the leaf margin. The
same filtering and parameterization that was used for the studies on rop2 mutants
was applied. Results showed values that were mostly insignificantly different across
development. The total pavement cell number varies insignificantly from week to
week (Figure 8A), whereas lobing, lobe height, and 3D surface area show significant
differences between weeks 5 and 6 of development (Figure 8BCD).
Figure 8. wt epidermis developmentally. Analyses were performed on the entire
data set of a given area of the plant surface. A. Number of cells were counted per
unit area after flattening and filtering the surface based on depression motifs that
were at least 6% of the highest peak and at least 1% of the overall surface area
(p=0.246). B. Number of lobes per unit area were counted using height motifs
generated using an area of less than 0.1% of the total surface area (p=0.0006). C.
Average lobe height per unit area was measured from the center maxima of the lobe
motif (p=0.008) D. Three-‐dimensional surface area was measured across the unit
area of data taken for each data set taken (p=0.0013).
Discussion and Conclusion
Studies on Rop2 Mutants
From the mutant studies of rop2, a picture begins to emerge of the
morphological differences between the mutant and wildtype. Since the overall
pavement cell number remains constant between the mutant and the wildtype per
unit area, it can be said that although there are some obvious changes in lobe
number, lobe height and overall surface area, the average 2D area that a given
pavement cell occupies must remain relatively constant. This is not true of the 3D
area. With an increase in 3D surface area, lobe number, and lobe heights, it can be
said that the wildtype is in generally more “lumpy” than the mutant, with more
incidents of height maxima, generating more lobe motifs and a greater overall
surface area. This is not to say the level of interdigitation in rop2 is less than the
wildtype, but that lobing is less exaggerated in the mutant so much that local
maxima begin to disappear. These results are not surprising in that it has been
shown that rop2 carries a defect in microtubule and microfilament arrangements
that impact pavement cell morphologies, and mutants were reported to display a
decrease in lobing in two-‐dimensions (Fu, et al., 2005).
Studies Across an Entire Plant
In looking at the entire A. thaliana leaf epidermis, several trends were
apparent. Isotropically, having the directions of 0°, 45°, 90°, and 135°, showing a
strong bias (Figure 8) indicates some directionality in the surface. Since the leaf was
viewed in the same position with the central vein always oriented in a north-‐south
fashion, these angles show some disposition to the orientation of cells at an angle
with or in line with the central vein. The angled dispositions may be a result of the
radiating veins that branch from the central vein at approximately 45°.
Analyzing 3D surface area, lobe height, lobe number, and pavement cell
number, the similar inverse bell curve trend can be seen in all cases, from old to new
leaves. Old and young leaves tend to be smaller and contain more compact
pavement cells, giving rise to a greater 3D surface area due to a greater number of
cell-‐cell valleys and greater number of pavement cells and number of lobes (in this
case the number of pavement cells outweighs the increase in lobing that is seen with
greater size of pavement cells). The increase in height seen may be a result from the
overall compactness of the pavement cells, having not yet fully expanded. For
placement within a leaf, across all leaves, the most distal and proximal regions have
greater numbers of pavement cells and more lobing, but a decrease in 3D surface
area and lobe height. In this case, the larger pavement cells of the more central
regions of the leaf have a greater height than those at the periphery, exaggerating
the cell-‐cell valleys and local undulations, taking up a greater surface area. These
two opposing trends can be seen in Figure 9. The overall inverse bell curve can be
seen across the entire graph for 3D surface area, illustrating pavement cell number
outweighing the factors from large pavement cells. The local undulations in the
curve indicate a movement from proximal to distal locations within a leaf, showing
the large pavement cell factors outweighing the small pavement cell factors.
Figure 9. 3D Surface Area leaf*placement graph. The x-‐axis numbers indicate
both leaf and placement in an increasing fashion from both proximal to distal and
both old to new leaf (ex. numbers 1-‐3 indicate the proximal to distal positions on
leaf 1, the numbers 4-‐6 indicate the proximal to distal positions on leaf 2…the
numbers 11-‐15 indicate the proximal to distal positions on leaf 4, etc.)
900
950
1000
1050
1100
1150
1200
1250
1 7 13
19
25
31
37
43
49
55
61
67
73
79
85
91
97
104
110
116
122
128
134
140
146
152
158
164
170
176
182
188
194
200
206
212
218
224
3D SA (µm²E2)
leaf*placement
Studies on Leaf Six Developmentally
Departures from results predicted for the developmental survey are most
likely due to specimen maturities being overly biased in the direction of too mature
to detect significant differences in pavement cell number. The relative decrease in
lobing and surface area are positively correlated. This observation is readily
rationalized, since lobing measurements are based on local height maxima, the less
“bumpy” the surface is, the lower the measured surface area is expected to be. In
addition, the height decrease observed between weeks five and six correlates
positively with a decrease in lobe number. It can be extrapolated that late in
development (between weeks five and six), leaf six undergoes a physiological-‐
morphological transition that flattens, but does not expand its pavement cells. This
flattening may be attributed to the removal of water to other still developing parts
of the plant, resulting in a decrease in turgor pressure from the water vacuole. This
also could be explained by the increase in cellulose in the cell wall of as pavement
cells develop, increasing their ability to resist turgor pressure expansion.
Implications for Future Research
Optical topometry is a high throughput tool that shows terrific promise for
enabling large scale sampling of plant epidermal surfaces. For taking cell censuses,
pavement cells can be identified and counted from Arabidopsis and undoubtedly
most other species, Arabidopsis being especially challenging with its highly
irregular, jigsaw puzzle epidermis. We have made progress in applying OT to
identifying stomata, but more work, and possibly purpose-‐written software, is
needed for this to become as reliable as it is for pavement cells. By creating a binary
image from the original Arabidopsis pavement cell filtering protocol, stomata can be
identified by the naked eye. Machine counting is therefore at least theoretically
within reach, although more work needs to be done to optimize it (Figure 10). With
automated counting of both stomata and pavement cells in hand, stomatal indices
and densities can be determined essentially instantaneously, massively accelerating
the quantitative, cellular phenotyping of plant epidermises for large scale genetic
studies.
In addition to greatly facilitating cell census taking, OT opens up barely-‐
explored opportunities for characterizing novel surface features with high precision.
For example, lobe analysis has never before been performed on a plant epidermis in
the z-‐dimension and represents a phenotype ripe for genetic analysis. In addition,
three-‐dimensional surface area is a novel parameter with potentially valuable
implications for modeling the plant-‐air interface. Finally, all measurements derived
from OT can be logged in high-‐throughput fashion, enabling large scale explorations
of these heretofore cryptic plant phenotypes.
Figure 10. Binary image of epidermal surface. Pavement cells are colored and
cell-‐cell boundaries are in light yellow. The binary nature is cell body and cell wall.
*Indicates a stomata that can clearly be seen and possibly isolated automatically in
the future.
Acknowledgements
I would like to thank Dr. Tom Jacobs and Miranda Haus for all of their help
along the way of this project in guiding my research. Miranda Haus ran all of the
statistics. I would also like to thank Chris Wichern (Nanofocus, USA) for providing
the µSurf Explorer instrument, the µSoft Analysis Premium software and training in
the use of both the hardware and software.
*
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