lab report microrna + nutrients

Nicole Celani Biol 220/ Section 012T.A. Laura Bennett 3/6/2012

Title:

Investigating microRNA expression by varying nutrient concentration available to Arabidopsis

thaliana

Introduction:

Arabidopsis thaliana is the model organism used for investigation of miRNA expression

because its entire genome has been sequenced (Weems 362–369). This organism also has a short

life cycle and grows relatively quickly with restricted space which makes it useful for lab

research (Weems 362–369). The nutrient concentrations that varied in this study were

phosphorus and sulfur. These nutrients are specifically varied because they are considered

macronutrients that are required for plant growth (Axtell). Phosphorus is a component of nucleic

acids, phospholipids, ATP and coenzyme. Sulfur is also a component of coenzymes as well as

proteins (Axtell). These are important nutrients for research because macronutrient such as

sulfur and phosphorus are limiting for plant growth and are often added via fertilizers to soils

(Axtell). Plants respond to varying levels of nutrient concentrations by controlling their gene

expression. Why waste energy creating proteins involving sulfur when there is no sulfur

available to the plant? To prevent this, plants control gene expression via miRNA which

degrades mRNA that is creating un-useful proteins. The function of miRNA is to bind to single

stranded mRNA creating double stranded RNA. The plant recognizes the double stranded

mRNA as foreign and breaks down the complex. This acts as a negative post-transcriptional

control (Axtell). The four microRNAs used for this investigation were miR156, miR395,

miR399 and miR398. The developmental regulator, miR156, has no nutrient requirement and

would be expected to show no change due to nutrient levels changing (Hsieh 2120-2132).

miR399 is up-regulated during phosphate starvation and thus targets genes in phosphorus uptake


and metabolism. (Hsieh 2120-2132). miR398 is regulated when there is Copper/Zinc starvation,

targeting the enzyme copper/zinc superoxide dismutases (Bouché 684–686). This stress

responsive miRNA has low levels of expression in both low sulfur and phosphorus environments

(Bouché 684–686). Lastly, miR395 depends on sulfur concentrations and targets mRNAs

involved in sulfur metabolisms (Hsieh 2120-2132). These miRNAs should show effects due to

the nutrients limitations and this is why they were chosen.

The purpose of this study is to examine differential gene expression under low nutrient

levels of sulfur and phosphorus. The procedure for this experiment was to plate Arabidopsis

thaliana on three mediums; full media, low phosphorus and no sulfur. The miRNAs were then

extracted from seedlings using a Qiagen kit. The data was then analyzed using qt-PCR analysis.

Results:

Data was collected for three graphs throughout this investigation. Figure 1, 2 and 3

represents the normalized relative accumulations for miR156, miR398, miR399 and miR395

under low phosphorus and low sulfur conditions. Figure 1, 2 and 3 represent data from a

previous study, section 012 data and data collected from the entire 240 class, respectively. In all

three replicates of the investigation miR156 showed very little up regulation. Figure 1, Figure 2

and Figure 3 show a very low and minute expression of miR156. However, Figure 3 shows a

very low level of expression under low sulfur conditions compared to figures 1 and 2. miR395

showed extreme up regulation across all three replicates under low sulfur conditions. Under low

phosphorus conditions miR395 showed no up regulation across all three graphs. miR398

showed repressed expression in both low sulfur and low phosphorus conditions across all three

sample sets. However, the class and section data showed a lower level of expression of miR398

during low sulfur then low phosphorus conditions compared to the previous study. Lastly,


miR399 showed higher levels of expression under low phosphorus conditions across all three

sample sets. All three figures also correlate in low levels of miR399 expression during low

sulfur conditions.

Discussion:

When examining differential gene expression under low phosphorus and low sulfur

conditions each miRNA had different responses to the nutrient concentrations as expected.

mir156 was expected not to have been regulated by nutrient suppression because it is not

involved in phosphorus or sulfur processes (Hsieh 2120-2132). This corresponds well to all

three graphs, in that there are low levels of expression in all data sets for both nutrient

deficiencies. This shows that miRNAs are specific to target certain functional machinery for

degradation. miR395 showed extreme up regulation of expression across all three sample sets

for low sulfur conditions. This correlated exactly with what would be expected considering the

function of miR395 is to target mRNAs involved in sulfur metabolism when sulfur is not present

(Hsieh 2120-2132). miR395 is not expressed under low phosphorus conditions because it does

not function in degradation of phosphorus machinery and this is also supported by the graphs.

When considering miR398 it shows low levels of expression across all three data sets. Knowing

the expression of miR398 is to be repressed under low sulfur and phosphorus conditions the

graphs support the observation of low expression levels (Bouché 684–686). The cell is

preventing the breakdown of CuZn-oxide dismutates by suppressing the formation of

miR398(Bouché 684–686). Lastly, miR399 was up regulated in low phosphorus conditions

compared to low sulfur conditions across the data sets. miR399 functions to cause the

degradation of machinery involved in phosphorus uptake and metabolism under low phosphorus

conditions to conserve energy and this is reflected in all three figures (Hsieh 2120-2132).


miR399 was not up-regulated in low sulfur conditions because degradation of this specific

machinery is not required. On a full media plate all usual machinery and miRNAs were present

in natural concentrations when all nutrients were present.

When considering all three data sets it seemed that the collection of all 33 sections in the

class 240 data had the best correlation to the functions of each miRNA. This is most likely due

to the large set of replicates collected for this graph compared to the other two data sets. Sources

of error may have occurred in many steps along the procedure. I specifically performed a low

phosphorus experiment in wells C7-C12 which resulted in faulty data. These non-normal values

may have been due to errors in the procedure. This may have been due to lack of starting tissue

in low phosphorus mediums, because the growth was very limited. Errors may have occurred

during RNA extraction, PCR amplification, lack of starting tissue and human error. Also,

introduction of RNases may have contaminated samples during RNA extraction and not

thoroughly grinding plant tissue.

This is important to the relative sulfur and phosphorus conditions in soils used for

farming and how this is effecting plant growth in agriculture. These macronutrients have

dramatic effects on plant growth and this research establishes how molecularly these nutrients

are required for plant growth. This research also provides insight to the functions of the

microRNA involved in specific nutrient deficiencies. This research leads to further investigation

of the effects of adding sulfur and phosphorus in large quantities to mediums instead of low

concentrations. Measuring the results of different levels of miRNA expression and growth rates

would be helpful information in plant growth. This would be useful to understand under what

exact concentrations of macronutrients plants are growing at optimum rates. Particularly, looking

more closely at miR398 because this had experienced down regulation and what its function is


when these nutrients are present. Observing different microRNAs that regulate gene expression

help to understand nutrient requirements in plants.

Materials and Methods:

Arabidopsis thaliana seeds were plated on three different media types; low phosphorus,

low sulfur and a full media plates. The control in this experiment was the full media plate. The

independent variable manipulated in this study was the media type that the seeds were grown on.

The dependent variable measured was the varying levels of miRNA expression. My lab partner

and I did a low phosphorus plate. The plates were then allowed to grow for two weeks. After

growth the plants were collected with sterilized tweezers and grinded using a lysis mix and a

pestle. Next, the kit used for isolating the small RNAs was a Qiagen kit following the

manufactures protocol. The microRNAs were then run in the thermocycler performing reverse

transcription reactions to convert the RNAs into single-stranded complementary DNAs.

Reverse Transcriptase Master Mix was used for the reverse transcription reactions. Lastly,

quantitative real-time polymerase chain reaction (qt-PCR) was used to analyze the RNA levels.

Every media type was analyzed using this procedure and U6 was used as the reference gene for

analysis. A U6 Master mix and miRNA master mix were used for analysis of each media type.

The four primers used for analysis were miR156, miR395, miR398 and miR399. My lab partner

and I used miRNA primer 395. The efficiencies values, E, were then obtained from the previous

study (data shown in figure 1) and was not actually calculated. From this information the cycle

threshold, Ct, values were calculated and used to calculate the normalized relative abundances of

each miRNA. These abundances were then used for analysis of the varying levels of miRNA

expression in low sulfur and low phosphors conditions.


Figures: All blue bars are representations of median RAn values of miRNAs in low

phosphorus conditions and all red bars are median RAn values of miRNAs in low sulfur

conditions.

Figure 1: The bar graph is a representation

of the normalized relative accumulation

values for the four miRNAs for a previous

study. The graph compares the regulation in

both low sulfur and low phosphorus

conditions.

Figure 2: The bar graph is a representation

of the normalized relative accumulation

values for the four miRNAs for Section

012’s Data. The graph compares the

regulation in both low sulfur and low

phosphorus conditions.

Figure 3: The bar graph is a representation of the normalized relative accumulation values for

the four miRNAs for all 33 sections of class 240’s data. The graph compares the regulation in

both low sulfur and low phosphorus conditions.

miR156 miR395 miR398 miR3990.01

0.1

1

10

100

1000

LowPLowS

The median RAn values of a Previous Study’s Data

The median RAn values of Section 012 Data

The median RAn values of Class 240’s Data

miR156 miR395 miR398 miR3991

10

100

1000

10000

LowPLowS


References:

Bouché, Nicolas. "New insights into miR398

functions in Arabidopsis." Plant Signal

Behav.. 5.6 (2010): 684–686. Web. 6 Mar.

2012.

<http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001559/?tool=pmcentrez>.

Hsieh, Li-Ching, Shu-I Lin, Arthur Chun-Chieh Shih, June-Wei Chen, and Wei-Yi Lin.

"Uncovering Small RNA-Mediated Responses to Phosphate Deficiency in Arabidopsis

by Deep Sequencing." Plant Physiol.. 151.4 (2009 ): 2120–2132. Web. 6 Mar. 2012.

<http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2785986/>.

“microRNA and Plant Nutrition” Axtell, M. Burpee, D. , and Nelson, K. Department of Biology,

The Pennsylvania State University, University Park, PA. (2012)

Weems, Danforth, Neil Miller, Margarita Garcia-Hernandez, Eva Huala, and Seung Rhee.

"Design, Implementation and Maintenance of a Model Organism Database for

Arabidopsis thaliana ." Comp Funct Genomics. 5.4 (2004): 362–369. Web.

<http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447457/>.

miR156 miR395 miR398 miR3990.01

0.1

1

10

100

1000

10000

LowPLowS

lab report microrna + nutrients

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