Dylan Easterday

Lab Partners: Samuel Payne, Angelique Crawley, Zohra Anwar

Lab Report 2

Biology 10100 Section 6XX2

10/30/16

Effect of Food Source on Enzymatic Activity in C. maculatusAbstract: Hypothesis and Justification

As an agricultural pest, Callosobruchus maculatus, or the cowpea seed beetle (figure 1),

is ubiquitous. This organism has habitat on every continent of the world except for Antarctica

and is a pest of the legume species often grown as food sources in regions of Africa and Asia (Li

et al 2016). Callosobruchus is of the order Coleoptera, which

includes all beetles and weevils, and is the largest order in all the

animal kingdom: containing amazing variety and an estimated

30% of all animal species on earth (Meyer 2016). This variety

and distribution around the globe suggests that species like C.

maculatus may be highly specialized to exploit specific food

sources, and adapted to do so.

This organism is model example of a significant pest to the crops of Mung Beans and

Cowpeas, Vigna radiata and Vigna unguiculata repectively (CCNY Department of Biology 63).

To prevent damage to crops or stored seeds that reduce yield, farmers will often employ the use

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Figure 1 Illustration of morphology of C. maculatus showing sexual dimorphism. (Blumer and Beck 2016)

logarithmic The equation represents the value of absorbency in AU (y) for a given value of concentration of the BSA solution in µg/mL.

of organophosphate pesticides. One such pesticide is the compound known as malaoxon (figure

2) which works to eradicate these pests through the action of acetylcholinesterase (AChE)

inhibition. AChE is a critical component in the cycle of excitation and inhibition of neurons,

including those responsible for motor functions. After acetylcholine neurotransmitters (ACh) are

released from the terminal end of the excited neuron, they bind

at receptor sites in the receiving neuron and trigger excitation,

thus continuing the signal. AChE then ends the signal by

cleaving ACh at the receptor site into molecules of choline and

acetate. Inhibition of AChE by organophosphate pesticides

results in a breakdown of this cycle and endless muscle

contraction in the organism – resulting in death (CCNY Biology

Department 63-64).

Some experimental evidence is available to suggest that because of the structural

similarities between manufactured pesticides like malaoxon and natural compounds present in

Vigna, these pests may have developed some adaptive ability to resist the effects of

organophosphate pesticides, according to studies referenced by the department (CCNY Biology

Department 65). Increased resistance may result in increased use of pesticides with diminishing

effectiveness, loss of crop yield, and high economic impact in areas that depend on trade of these

legume crops. Additionally, there may be some relationship between the level of resistance and

the food source of the beetle larva (Liang et al. 2007).

Our investigation focused on the potential effect of the food source of C. maculatus on

enzymatic activity that could result in detoxification of organophosphate AChE inhibitors. Our

two-tailed hypothesis was that the food source for C. maculatus would have some effect on the

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Figure 2: Structure of malaoxon, an organophosphate pesticide (NCBI 2016).

resulting enzymatic activity in the organism with a null hypothesis of no change in enzymatic

activity between food sources.

Experimental Design

Our experimental design was set up to include two experiments split by the substrate

tested (alpha and beta) with the food source as our independent variables (cowpeas and mung

beans). In both experiments we set out to find the potential relationship between the food source

and the effects on our dependent variables, ANAE and BNAE activity shown in the beetle

samples by test with relevant substrates: α-naphthyl acetate

and β-naphthyl acetate. These substrates served as proxy

indicators of enzymatic activity targeting structures like that

of organophosphate AChE inhibitors (CCNY Biology

Department 65-66). We kept a standardized variable as the

strain of C. maculatus, known as LB. Within each

experiment on the respective food sources, there were 2 treatment levels and 1 replication. Our

sample sizes were as follows: βNAE-cowpea replication had a sample size of 12, βNAE-mung

bean replication had a sample size of 17, αNAE-cowpea had a sample size of 17, and αNAE-

mung bean had a sample size of 18.

As a group, we followed the procedure set in the lab manual, starting first with a crude

protein extraction then a colorimetric enzyme assay testing enzymatic action on both αNA and

βNA by detection of byproducts with a dye – thus indicating activity in the form of changes to

absorbance (AU), and finally adjusting for variation in beetle size and differences possible in the

protein extraction by a protein assay. The protein content adjustment was completed using a

calibration curve to find the relationship between absorbance in the colorimetric assay results to

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Figure 3 Experimental Setup of Protein Assay and Serial Dilution

calculate protein content in our samples (figure 4). An example of the calibration calculation is

as follows. In our sample beetle number 1, a female, we had observed an absorbance reading of

0.282 AU while testing for αNAE in the colorimetric assay, and 0.156 AU while testing for

βNAE similarly. The colorimetric assay was performed using the previously prepared crude

extracts by measuring the spectrophotometric absorbency of the samples after the addition of 800

µL of Bradford dye reagent. The Bradford test works by the mechanism of the dye binding

primarily to the arginine residues left by the reaction between the crude extract and the Bradford

solution (Experimental Biosciences 2016). The resulting bond changes the structure of the dye,

causing a change in the wavelengths of light absorbed and the appearance of color. This

absorbency is again measured using the spectrophotometer. By using the calibration curve

obtained with the results from the graph of the serial dilution, we could apply the equation found

to calculate the protein content of our sample from the absorbance reading we observed earlier in

the experiment. The relationship between protein concentration (x value) and absorbance (y

value) is given by the equation y=0.2913 ln (x )−0.9053. Therefore, we could solve for the

unknown protein content by applying the known absorbance value and rearranging the equation:

x=e0.282+0.905

0.2913 and then multiplying the result by 0.050 mL to adjust our units to the volume of

each sample, for a final value of 4.36 µg of protein in the sample. This result was then used to

find a rate of enzymatic activity (αNAE and βNAE) by using the formula: Absorbance( AU )

ProteinContent (µg).

From this, αNAE activity level measured at 0.065 AU/µg and 0.36 AU/µg for βNAE for our

sample organism 1.

Finally, in our methods, the results were analyzed using a two-tailed t-test and the results were

compared for both the αNAE and βNAE experimental results.

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Our experiment prediction was that, controlling for the difference in protein content

across samples, we would observe a difference in either αNAE or βNAE activity based on the

food source of C. maculatus – either Vigna radiata or Vigna unguiculate.

Results and Data Analysis

As can be seen in figure 5 the

resulting data on the average αNAE

activity among the samples of beetles

feeding on mung beans and cowpeas

shows little difference and a wide range

for the standard deviation within the

sample. The mean for the sample of αNAE

– mung bean was 0.0893 AU/µg with a

standard deviation of 0.0703 AU/µg and

the mean for αNAE – cowpea was 0.0909

AU/µg with a standard deviation of 0.1309

AU/µg.

Table 1: t-test results for the ANAE experiment comparing food sources on enzymatic activity.

ANAE T-TEST RESULTSt-calculated 0.0567

t-critical for 95% confidence level >2.03, <2.04Degrees of Freedom 33

Confidence Level <80%

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Figure 4 Graph of Mean ANAE Activity comparing food sources. The error bars show the standard deviation for each treatment group.

Food Source

Mung bean Cowpea

After conducting a two-tailed t-test, the resulting data analysis (table 1) shows a

calculated t of 0.0567. Far off from the t-critical value for these data of between 2.03 and 2.04.

With 33 degrees of freedom, the estimated confidence level is below 80%.

Figure 6 shows the resulting means of

the samples of both experiments testing

for βNAE activity. The samples on the

mean βNAE activity from beetles

feeding on mung beans was 0.0159

AU/µg and 0.0557 AU/µg for those

feeding on cowpeas. The standard

deviations of these data were 0.0097

AU/µg for the mung bean samples and

0.1044 AU/µg for the cowpea samples.

The two-tailed t-test comparing samples

across food sources (table 2) shows a t-

calculated value of 1.58, falling short of

the t-critical of 2.05. With 27 degrees of freedom within the samples, our confidence level in

these data is greater than 80% but less than 90%.

Table 2: t-test results for the BNAE experiment comparing food sources on enzymatic activity

BNAE T-TEST RESULTS Column1t-calculated 1.58

t-critical for 95% confidence level 2.05Degrees of Freedom 27

Confidence Level >80%, <90%

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Figure 5: Graph of mean BNAE activity experiment comparing food sources. The error bars show the standard deviation for each treatment group.

Food Source

Mung bean Cowpea

Discussion and Conclusions

The results of the experiments here do not support our hypothesis or predictions. While some

level of difference in enzymatic activity is hinted in the results here, the data analysis clearly

shows that the differences are not statistically significant. There are several possibilities as to

why our data fail to show a real difference in enzymatic activity. One possibility is that, due to

our relatively small sample sizes, errors in protein or absorbance readings may have skewed our

data and resulted in off readings. What is evidenced by our findings is that resistance to

pesticides in C. maculatus is not directly related to enzymatic activity, but if present, may be due

to some other environmental, evolutionary, or adaptive function. To speculate, since enzymes are

proteins that often function at optimal levels at a given temperature, further experiments may be

designed to test whether higher or lower temperatures have any effect on the readings of the

enzymatic assays. Additionally, these tests are meant to represent the enzymatic activity on

AChE inhibitors by using compounds that are structurally similar, but not identical, to

organophosphate toxins like malaoxon. Further study on the exact structure and function of these

AChE inhibitors may be needed.

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Literature Cited

Blumer, Lawrence. Beck, Christopher. (2014, June) A Handbook on Bean Beetle,

Callosobruchus maculatus. www.beanbeetles.org/handbook.

Department of Biology, City College of New York. Course Supplement for Biological

Foundations I Bio 10100. Fall 2016.

Experimental Biosciences. Resources for introductory and intermediate level laboratory courses.

http://www.ruf.rice.edu/~bioslabs/methods/protein/bradford.html (accessed Nov. 29,

2016)

Liang, P. Cui J-Z., Yang, X-Q. and Gao, X-W. 2007 Effects of host plants on insecticide

susceptibility and carboxylesterase activity in Bemisia tabaci biotype B and greenhouse

whitefly, Trialeurodes vaporariorum. Pest Management Science 63: 365-371.

Meyer, John R. "Classification & Distribution." Coleoptera. General Entomology, 28 Mar. 2016.

Web. 2 Nov. 2016.

National Center for Biotechnology Information. PubChem Compound Database; CID=15415,

https://pubchem.ncbi.nlm.nih.gov/compound/15415 (accessed Nov. 2, 2016).

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