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Examining the expression levels of mi156, mi395, mi398, and mi399 in phosphate and
sulfate deficient environments
Joshua T. Bram
Biology 240M - Section 001M
TA – Hongchen Cai
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Introduction
The population of the planet is rapidly rising, and as a result, the demand for
increased productivity of grain crops is at its zenith. In 1993 alone, 1.6 billion tons of
rice, maize, and wheat were produced, yet this was still not enough to satisfy the
nutritional requirements of many developing countries (Oerke and Dehne, 1997). Crop
productivity is further reduced annually as a result of nutrient deficient soils, which are
further taxed by the added burden of an increasing crop demand. In Africa alone, up to
75% of agricultural land is nutrient deficient, which greatly contributes to a lack of
nutrition and creates the additional challenge of rising out of poverty (Cordell et al.,
2009). The effects of nutrient deficiency on plant growth can be drastic, and often include
growth inhibition and decreased crop yield (Kruzska et al., 2012). The macronutrients
phosphorus and sulfur in particular are vital nutrients in plants. Phosphorus, in the form
of HPO42-, is an integral part of nucleic acids, phospholipids, and ATP, while sulfur, in
the form of SO42-, is an important atom in the amino acid cysteine and several coenzymes
(Reece et al., 2011). A decrease in concentration of both macronutrients is known to lead
to growth inhibition, and plants have evolved several mechanisms to increase the uptake
and storage of the nutrients.
To regulate the concentrations of these nutrients and to increase their uptake,
plants utilize small fragments of RNA called micro RNAs. These fragments are encoded
by miRNA genes, which are initially transcribed in a stem-loop structure. After cleave to
produce the active miRNA, the miRNA binds to a protein forming an RNA-induced
silencing complex-like structure with the ability to regulate gene expression (Bartel and
Bartel, 2003). The miRNAs transcribed are complementary to particular gene RNA
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transcripts, whose expression can be up regulated or down regulated based upon external
stimuli. Upon binding another transcript, the RNA molecule will be degraded and further
translation will be blocked.
Of particular interest to this study are the miRNAs: mi156, mi395, mi398, and
mi399. These miRNA molecules are known to have various effects on plant development
and nutrient stress response. Mi156 is known specifically to be involved in the regulation
of salt-stress response, cold response, UV light response, and flowering (Khraiwesh et al.,
2012; Sunkar, 2010). The flowering response of mi156 targets SPBL2 and SPBL10 genes,
which actually serves to suppress flowering, making mi156 an miRNA whose expression
is less likely to be affected by nutrient deficiencies (Kidner and Martienssen, 2005).
Mi395 functions to increase the expression of low-affinity sulfate transporters such as
SULTR2;1 as well as ATP Sulfurylase genes, which assimilate sulfur (Kruszka, 2012).
Due to its function, it is expected that mi395 expression will be strongly increased in
sulfate-deficient environments. Mi398 functions in the regulation of proteins that
detoxify reactive oxygen species, such as Cu/Zn-SODs and other superoxide dismutases
(Sunkar, et al., 2007; Kruszka, 2012). In the presence of reactive oxygen species, mi398
expression is down regulated, as it normally cleaves the SOD RNA transcripts. Because
mi398 activity is not directly related to nutrient stress responses, it is again hypothesized,
as with mi156, that mi398 expression will not be greatly affected by phosphate or sulfate
nutrient deficiencies. The final miRNA of interest, mi399, helps to regulate phosphate
homeostasis in a signaling network that leads to the expression of high-affinity phosphate
transporters for increased phosphate uptake (Kruszka, 2012). It is therefore predicted that
phosphate deficiencies will lead to an increase in mi399 expression.
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By examining the expression of levels of the four miRNAs, this study will help
answer the question of how nutrient stress impacts the expression of miRNA controlling
nutrient uptake and flowering in the model organism Arabidopsis thaliana (Ward et al.,
2014). The results will also contribute to a larger question of what miRNA expression
levels of various miRNAs will lead to optimal crop yield in various stressful
environmental conditions such as drought, heavy rainfall, temperature extremes, and
nutrient stress. By conducting such this study, the researchers will be able to adapt
current miRNA purification and qRT-PCR procedures for use in determining miRNA
expression levels.
This experiment will utilize the model organism Arabidopsis thaliana.
Arabidopsis was chosen primarily because of its short life cycle, small size, and ease with
which it is cultured in lab, among other factors (Reece et al., 2011). However, the
ultimate goal of the study is to obtain results that can be generalized to wheat, which is a
major agricultural crop. A study for wheat that focuses only on the miRNAs deemed
important for nutrient stress will then allow scientists to better understand crop responses
to nutrient deficiencies. These results will then hopefully lead to methods of increasing
crop yield in those stressful environments.
As stated previously, it is expected that mi395 expression will be increased in
low-sulfate conditions, mi399 expression will be increased in low-phosphate conditions,
and that mi156 and mi398 expressions will be relatively consistent with control plants.
These results are predicted based upon the functions of each individual miRNA, with the
mi395 and mi399 specifically impacting the uptake and homeostasis of sulfur and
phosphate respectively (Sunkar et al., 2007).
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Materials and Methods
Materials for the experiment consisted primarily of petri dishes, Arabidopsis
seedlings, and media containing three types of nutrients: full medium, low phosphate, and
no sulfur (Ward et al., 2014). Also required were miRNA extraction materials from a
Sigma mirPremier microRNA isolation kit, as well as pulsed reverse transcription
reaction mix solutions. This utilized a primer, dNTP, and water master mix as well as a
reverse transcriptase master mix. Once this step was performed, quantitative real time
PCR materials were utilized, with two separate master mixes for a control and the actual
miRNA. The final requirement was a computer with Microsoft Excel for data analysis.
The experimental setup consisted of a pair of individuals plating approximately
30-100 seedlings on two petri dishes containing the same media type. The three media
used to test miRNA expression in nutrient deficient environments consisted of a full
medium (1XMS with 1.25mM of phosphate and sulfate) control, low phosphate (1XMS
low phosphate with 0.01mM phosphate), and no sulfur (1XMS no sulfur with 0.0mM of
sulfate) media. Across a group of six, the three media were plated in replicates of two.
After plating, petri dishes were left in the dark/cold for three days before being moved to
a growth chamber in Wartik lab at Penn State University for two weeks (Ward et al.,
2014).
Following the initial growth period, seedling tissue was prepared for miRNA
extraction using approximately 40 seedlings for the full and no sulfur while roughly 53
seedlings from the low phosphate plates (Ward et al., 2014). These tissues were ground
thoroughly and mixed with 750L of lysis mixture, then centrifuged to pellet out any
other cellular debris, isolating a supernatant containing the miRNA. This process was
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completed twice for each media type for a total of six plates across the three treatment
groups. Complete miRNA extraction was conducted following the approved protocol for
the Sigma mirPremier microRNA isolation kit (Sigma-Aldrich). This extraction was used
to isolate mi156, mi395, mi398, and mi399 so that expression levels across the three
treatment groups could be analyzed.
Using the extracted miRNA samples, pulse reverse transcriptase was performed to
generate a cDNA library for eventual quantitative real-time PCR of the products.
Initially, four L of miRNA sample were mixed with a primer, dNTP, and water mastermix and heated at 65˚C for five minutes (Ward et al., 2014). Once this step was complete,
6.35L of reverse transcriptase master mix were added, and a pulsed reverse transcription
was performed on a thermal cycler in an effort to generate the cDNA library.
Once the cDNA library had been generated, quantitative real-time PCR was
performed on the replicate samples. Because PCR utilizes primers specific to each
miRNA gene to be isolated, different groups ran the qRT-PCR for different miRNAs.
Each pair then also ran the PCR on a U6 control primer set as well as two wells of
negative control. The master mixes composed 9L water and 10L SYBR Green master
mix by Qiagen for both master mixes (U6 master mix and microRNA master mix).
Specific to each master mix were the forward and reverse oligo U6 and miRNA primers,
with 1L of both forward and reverse primers added. 24 L of master mix was mixed
with 1L of cDNA in each PCR well for amplification and identification of each miRNA.
A Taq DNA-dependent DNA polymerase that is able to withstand the high temperatures
induced by the thermal cycler amplifies the cDNA present in each well to detectable
levels. This amplification ideally doubles the amount of DNA present initially in each
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well with every cycle. Over the course of 40 cycles, DNA levels should be amplified
significantly. The SYBR green probe acts by binding the double-stranded DNA
molecules in each PCR well, and fluorescing once bound so that the amount of miRNA
initially present can be determined (Ward et al., 2014). This PCR setup was repeated
across the three media treatments and across the four miRNAs of interest as well as the
U6 control gene.
In order to analyze the data, and obtain relative accumulations of miRNAs, which
was performed using Microsoft Excel 2008, the efficiency of the miRNA and U6 primers
used were first determined (Ward et al., 2014). This was accomplished by a series of
dilution steps with known dilution factors. The cycle threshold values for these dilution
factors were then plotted for each primer to obtain a slope that was used in the equation
E=10^(-1/S) to determine primer efficiency. Once the efficiency of each primer was
determined, the ∆Ct values of the samples were determined by subtracting the Ct value of
the miRNA in the full medium treatment from the Ct value in the low phosphate or no
sulfur treatment groups (∆Ct = Ctcontrol-Ctexperimental). This was done so that changes in
miRNA expression could be analyzed relative to the normal expression of those genes.
Following this step, the relative accumulation (RA value) of each miRNA was
determined from the following equation: RA = E∆Ct. However, another normalization step
had to be undertaken, as there is almost always unequal loading of samples into PCR
tubes, particularly with such small volumes of liquid. This was be corrected for by
calculating normalized relative accumulation (RAn), which is calculated by dividing the
relative accumulation of the target gene (one of the miRNAs) by the relative
accumulation of the reference gene, U6 (RAtarget/RAreference). The final analysis step took
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into account that there were two replicates for each sample, so the median of the two
normalized relative accumulations was found, and then all values were plotted by
treatment group as RAn vs. target miRNA.
No technique deviations from the lab manual or established protocols occurred, as
none were deemed necessary. Instructors performed the plating of the petri dishes with
seeds across different media and also finished pulsed reverse transcription to the cDNA
library. This was contrary to the lab manual in which students were instructed to
complete these steps, but timing of the experiment did not make this feasible.
Results
Legend: Three
treatment
groups (FM,
LP, NS) across
four-week
growth period
Week 4
Figure 1. Influence of full, low phosphate, and no-sulfur medium on plant morphology
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The images detail the effects of nutrient deficiency on plant morphology.
Specifically, it is apparent that the full medium plants were much greener with larger
leaves and taller, thicker stems than either of the other treatment groups. The low
phosphate plants were smaller with dark-colored leaves, but a more extensive root
system. The no-sulfur plants were paler and smaller with less vegetation (smaller leaves)
and fewer roots.
All qPCR reactions with negative controls for both the sample and section data
achieved Ct values that were either “undetermined” or appeared after cycle 36, indicating
that there was no contamination for those samples at any step.
Table 1. Median RAn values of sample data for low phosphate and no-sulfur treatments
Median RAn's
LowP
LowS
miR156
1.862930111
1.227683226
miR395
0.046397251
1158.413858
miR398
0.035445039
0.150537893
miR399
20.76552394
1.198111257
Table 2. Median RAn values of section data for low phosphate and no-sulfur treatments
Median RAn's
LowP
LowS
miR156
0.111820765
7.234385601
miR395
0.508479963
969.3807593
miR398
17.20884977
6.59568177
miR399
151.660697
7.92026409
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Table 3. Median RAn values of course data for low phosphate and no-sulfur treatments
Median RAn's
LowP
LowS
miR156
0.7733
1.0354
miR395
1.3411
751.4459
miR398
17.2088
2.1197
miR399
25.2056
0.7390
Changes in microRNA accumulation in
Arabidopsis seedlings grown on nutrientdeficient media (sample data)
Normalized Relative Abundance (log10)
10000
1000
100
LowP
10
LowS
1
0.1
0.01
miR156
miR395
miR398
miR399
Figure 2. Changes in microRNA accumulation in Arabidopsis seedlings grown on
nutrient-deficient media (sample data)
The sample data was obtained by Dr. Axtel at Penn State and provided by the
Teaching Assistant, Hongchen Cai. The data was obtained through qRT-PCR of cDNA
samples obtained from pulsed reverse transcription from extracted mina.
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Normalized Relative Abundance (log10)
Changes in microRNA accumulation in Arabidopsis
seedlings grown on nutrient-deficient media (section
data)
10000
1000
100
10
LowP
1
LowS
0.1
0.01
miR156
miR395
miR398
miR399
Figure 3. Changes in micron accumulation in Arabidopsis seedlings grown on nutrientdeficient media (section data)
The section data was obtained through qRT-PCR of cDNA samples obtained
through pulsed reverse transcription from extracted mina from plants grown on low
phosphate and no-sulfur media. Results were then analyzed for normalized relative
Normalized Relative Abundance (log10)
abundance of mi156, mi395, mi398, and mi399.
10000
Changes in microRNA accumulation in Arabidopsis
seedlings grown on nutrient-deficient media (whole
course data)
1000
100
10
LowP
1
LowS
0
0
miR156
miR395
miR398
miR399
Figure 4. Changes in microRNA accumulation in Arabidopsis seedlings grown on
nutrient-deficient media (whole course data)
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The course data was obtained through qRT-PCR of cDNA samples obtained
through pulsed reverse transcription from extracted miRNA from plants grown on low
phosphate and no-sulfur media. Results were then analyzed across all course sections for
normalized relative abundance of mi156, mi395, mi398, and mi399.
The results show greatly increased expression of mi395 in plants grown on nosulfur media as well as increased expression of mi399 in plants grown on low phosphate
media (Figures 2-4). Mi156 expression appears to have been constant relatively
unchanged by treatment status, while mi398 expression appears relatively unchanged if
not slightly increased. The sample data shows a 1000-fold increase in mi395 expression
with no-sulfur along with a 30-fold increase in mi399 expression with low phosphate
(Figure 2). These results are consistent with the findings from the section and course data,
although mi399 expression appears to be more highly expressed in the section results
than the entire course data and sample data (Figures 3-4). However, expression is still
increased significantly. Mi156 expression appears to remain relatively unchanged from
standard media across all three data sets. Mi398 expression is decreased in the section
data for both low phosphate and no-sulfur media 10-fold, but in the section in course
data, it was found that mi398 expression was increased in plants grown on both media.
The course data (Figure 4) for the expression levels of mi156, mi395, and mi399
appears to be consistent with published data indicating that the expression of both
miRNAs is increased in the presence of phosphate deficiency and sulfur deficiency
respectively (Kruszka et al., 2012). However, mi398 expression is not consistent with
previous literature findings, which would at the minimum expect no change in expression
levels on low phosphate and no-sulfur media. The sample data obtained by Dr. Axtel in
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fact appears to indicate that the opposite is true, and that mi398 expression is decreased in
response to nutrient stress.
Discussion
The results from this study are able to answer the question of how nutrient stress
affects miRNA expression levels in plants. Course data indicates increased expression of
mi395 in response to sulfur deficiency (Figure 4), which is supported in studies by
Kruszka et al. and Sunkar et al., and Sunkar (2010). Data also indicates increased mi399
expression in response to phosphate deficiency (Figure 4), again supported by Kruszka et
al., Sunkar et al., and Kraiwesh et al. The expression of mi156 was found to be
unchanged in response to nutrient stress (Figure 4), which is consistent with its role in the
regulation of plant flowering, a function unrelated to the uptake of nutrients. This is
consistent with a study by Bartel and Bartel (2003). The expression of mi398 was
increased in response to nutrient stress (Figure 4), which is inconsistent with its role as a
regulator of superoxide dismutase synthesis (Kidner et al., 2005). The results for mi398
expression were also inconsistent with previous findings by Dr. Axtel (Figure 2).
The results of mi398 expression would likely indicate some form of experimental
error. Such error could have resulted from improper isolation or PCR techniques. This is
unlikely though as the normalized relative accumulations of other miRNAs are consistent
with previously published results. There are few inconsistencies between section and
course data (Figures 3-4), and the only major inconsistency was with the expression of
mi398 between the course/section data and sample data. A potential source of this
inconsistency could be that the same strain of Arabidopsis was used in the most recent
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iteration of the study, while the sample data was obtained at a different time. Perhaps the
Arabidopsis seedlings used in the sample data study expressed different levels of miRNA
as a result of genomic differences. Other sources of error could have simply resulted from
poor techniques performed by students.
Further experiments could examine the functions of other miRNAs and their
impact on nutrient stress responses as well as the roles of miRNAs in regulating drought,
extreme temperature, and heavy rainfall responses. Another similar study could focus
specifically on either phosphate or sulfur deficiency across a broader array of treatments
ranging from zero nutrients to full nutrients with several intermediate treatments that give
a spectrum for a better understanding of miRNA regulation.
These findings go a long way to answering the question of how nutrient stress
impacts the expression of miRNAs, showing that mi395 and mi399 are up regulated as a
response as the plant attempts to increase nutrient uptake. The study also showed that
current qRT-PCR and extraction methods did not need to be altered to produce results
consistent with published data. The results can also be generalized and applied to help
understand what expression levels of miRNAs should be utilized for producing wheat
plants with optimal yield.
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Ward, A., Axtell, M. Burpee, D., and Nelson, K. (2014) “Using microRNA to enhance
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Pennsylvania State University, University Park, PA