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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 750L 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 master-

mix and heated at 65˚C for five minutes (Ward et al., 2014). Once this step was complete,

6.35L 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 9L water and 10L 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 1L of both forward and reverse primers added. 24 L of master mix was mixed

with 1L 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

Week 4

Figure 1. Influence of full, low phosphate, and no-sulfur medium on plant morphology

Legend: Three treatment groups (FM, LP, NS) across four-week growth period

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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 treatmentsMedian 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 treatmentsMedian 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 treatmentsMedian RAn's

LowP LowS

miR156 0.7733 1.0354

miR395 1.3411 751.4459

miR398 17.2088 2.1197

miR399 25.2056 0.7390

miR156 miR395 miR398 miR3990.01

0.1

1

10

100

1000

10000

Changes in microRNA accumulation in Ara-bidopsis seedlings grown on nutrient-deficient

media (sample data)

LowPLowS

Nor

mal

ized

Rel

ativ

e A

bu

nd

ance

(log

10

)

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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miR156 miR395 miR398 miR3990.01

0.1

1

10

100

1000

10000

Changes in microRNA accumulation in Arabidopsis seedlings grown on nutrient-deficient media (section

data)

LowPLowS

Nor

mal

ized

Rel

ativ

e A

bund

ance

(lo

g10)

Figure 3. Changes in micron accumulation in Arabidopsis seedlings grown on nutrient-

deficient 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

abundance of mi156, mi395, mi398, and mi399.

miR156 miR395 miR398 miR3990

0

1

10

100

1000

10000

Changes in microRNA accumulation in Arabidopsis seedlings grown on nutrient-deficient media (whole

course data)

LowPLowS

Nor

mal

ized

Rel

ativ

e A

bund

ance

(lo

g10)

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 no-

sulfur 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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References

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Plant Physiol, 132:1-9

Cordell, D., Drangert, J.-O., and White, S. (2009) The story of phosphorus: Global food

security and food for thought, Global Environmental Change. 19:292-305

Kidner, C.A., and Martienssen, R.A. (2005) The developmental role of microRNA in

plants, Current Opinion in Plant Biology. 8:38-44

Kraiwesh, B., Zhu, J.-K., and Zhu, J. (2012) Role of miRNAs and siRNAs in biotic and

abiotic stress response in plants, Biochimica et Biophysica Acta. 1819:137-148

Kruszka, K., Pieczynski, M., Windels, D., Bielewicz, D., Jarmolowski, A.,

Szweykowska-Kulinksa, Z., Vazquez, F. (2012) Role of microRNAs and other

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(2011) Soil and Plant Nutrition, In Campbell Biology. 9:791

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Ward, A., Axtell, M. Burpee, D., and Nelson, K. (2014) “Using microRNA to enhance

wheat crop yields in nutrient poor conditions”, Department of Biology, The

Pennsylvania State University, University Park, PA

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