Download Thesis-Codon Bias in Escherichia coli Cells

Playing Favorites: The Effects of Codon Bias in
Escherichia coli Cells
Victoria Mauro, American University
Dr. David Carlini, Biology Department
University Honors in Biology
Fall 2012
Playing Favorites: The Effects of Codon Bias in Escherichia coli Cells
Victoria Mauro, American University
Abstract
Codon bias is the unequal usage of synonymous codons in the protein coding genes of all
cells, including Escherichia coli. Though many hypotheses exist to explain the presence of codon
bias, the translational selection hypothesis, the most widely accepted hypothesis, posits that
codon bias was the result of natural selection working for translational efficiency based on the
concentration of certain tRNAs in a cell. The global translational selection hypothesis takes this a
step further and suggests that selecting for efficiency in one gene may affect the fitness of the
entire cell. In E. coli cells, two of the six leucine codons have the largest and second smallest
relative synonymous codon usage of all E. coli codons. Thus, these codons were targeted for
experimental mutation, and an ampicillin resistance gene was engineered, replacing the eight
preferred leucine codons with unpreferred codons. Both wild-type (WT) and mutant (mut8Leu)
cell strains were grown separately in the presence of ampicillin and tetracycline to test the local
and global translational selection hypothesis. Additionally, the strains were grown alongside
each other in the presence of ampicillin to competitively assess their fitness. It was found that
WT strains had higher growth rates and frequencies in the presence of ampicillin in both the
growth assays and competitive fitness experiments respectively. However, growth in the
presence of tetracycline did not provide any significant differences in growth. Thus, though
support was gathered for the local piece of the translational selection hypothesis, more work is
required to determine the validity of the global aspect.
Introduction
Codon bias, the unequal frequencies of codon usage in the DNA of all organisms, raises
many questions as to the mechanisms and organismal value of this phenomenon (Chamary,
Parmley, and Hurst, 2006). Though statistics would suggest that each codon would be found in
the genome with the same regularity, codon bias violates this assumption and instead the DNA of
each organism favors some codons for a particular amino acid above others (Charmary et al,
2006). Many hypotheses exist to explain the presence of codon bias, but the translational
selection hypothesis has become the most widely accepted since the discovery of codon bias in
the 1960s (Charmary et al, 2006). This hypothesis posits that, since codons interact most strongly
with one tRNA but can interact with more than one, the codons that bind most strongly to the
most abundant tRNA in the cell will be translated more quickly and accurately than codons that
bind most strongly with less prevalent tRNA (Hense, Anderson, Hutter, Stephan, Parsch, and
Carlini, 2010). In addition, favored codon bias in one gene may produce a positive effect on the
translation of other genes Kudla, Murray, Tollervey and Plotkin, 2009). If a particular gene has
many favored codons, those that interact most strongly with the most prevalent tRNA, ribosomes
will move more quickly down the mRNA, produce a more accurate protein, and ensure the
presence of many free ribosomes in the cell to translate other mRNAs (Kudla et al, 2009).
However, less favored codons will cause ribosomes to lag waiting for less prevalent tRNA, thus
lowering the number of free ribosomes available in the cell (Kudla et al, 2009). Therefore,
according to this hypothesis, codon bias affects not only single genes as they are translated, but
the entire cell and its ability to translate other genes.
The phenomenon of codon bias has incredible implications for medicine and evolutionary
biology, but only after it is truly understood. In a paper by J. Robert Coleman et al, researchers
1
manipulated the codons of the viral capsule in the polio virus (Coleman, Papamichail, Skiena,
Futcher, Wimmer, and Mueller, 2008). They used codons that were rarely seen in the human host
and discovered that in the rare-codon virus, infected cells produced fewer virus particles and
were less virulent than their wild-type counter parts. In essence, the virus could be attenuated by
manipulating the codons it used (Coleman et al, 2008). A similar finding was produced in a 2012
paper in nature, where researchers found that Schlafen (SLFN) 11, a human interferon implicated
in the human viral immune response, selectively inhibits the translation of HIV mRNA by
exploiting viral codon preference that causes ribosome pausing and inefficient translation, thus
suppressing selective viral proteins via transcript-intrinsic properties (Li el al, 2012). If
researchers can understand the effects of codon bias in cells, they may be able to harness it
against disease and in use for therapies.
In Escherichia coli, the codons for leucine present the largest disparity between favored
and unfavored codon usage of any codons in the genome. The favored leucine codon, CTG,
appears in the genome 2.96 times more frequently than expected, while the least favored leucine
codon, CTA, appears 0.22 times less frequently than expected (Table 1) (Carlini unpublished
data, 2012). Genome wide, these two codons have the largest and second smallest relative
synonymous codon usage of all E. coli codons, respectively (Carlini, 2012). If the global
translation hypothesis holds true, researchers can use this incredible discrepancy to create
notable fitness changes in cells after only a few days.
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To test this hypothesis, this experiment mutated 8 of the leucine codons of a pBR322
vector ampicillin resistance gene in E. coli cells REL606 and REL607. pBR322 is plasmid used
for its low copy number in cells. This low copy number meant that small changes in protein
production from the plasmid would be notable, as opposed to high copy number plasmids where
so much protein is produced that changes would not be necessarily detectable. pBR322 contains
both an ampicillin and a tetracycline antibiotic resistance gene, both of which are constitutively
expressed. The ampicillin resistance gene in pBR322 contains 33 leucine codons, 25 of which
are already CTA, the unpreferred codon. The other 8 leucine codons are the most preferred CTG
codon in the wild-type plasmid. A mutant 8 leucine ampicillin resistance gene (mut-8Leu-A mpR )
was created to test the efficiency of both local and global translation in mutant versus wild-type
2
(WT) cells. REL606
and
REL607
are
identical E. coli strains,
save for one difference;
REL606 can metabolize
arabinose and will turn
red upon doing so,
while REL607 cells
cannot. Thus, these two
cells strains were used
for indicator purposes,
as they would be easily
distinguishable
when
plated
on
media Figure 1. Experimental design of the coevolution assay. Replicate liquid E. coli
containing arabinose.
cultures containing equal amounts of wild-type (WT) and mut-8Leu-AmpR
Two
experi- genotypes will be grown in the presence of ampicillin. Cultures were grown
ments were used to test continuously at both 37°C and 30°C for seven to ten days, with serial transfers to
fresh media every 24 hours. Liquid cultures were sampled and plated on TA agar
for the effects of codon indicator plates to determine the number of red and white colonies, indicating the
bias both locally and different genotypes. Colony counts were analyzed for each time point to
globally. Initially, WT determine genotype frequency.
and
mut-8Leu-A mpR
cells were grown in separate test tubes and tested every hour for optical density to determine
growth rates. Strains were grown in media with both ampicillin and tetracycline, and growth
rates were compared among genotypes to determine the effect of codon mutation. The presence
of ampicillin tested for local effects of codon bias; The prediction was that mut-8Leu-A mpR
strains would grow more slowly because they had no preferred codons, while the WT would
grow more quickly because they had eight. The tetracycline media tested for a global effect of
codon bias. Because the tetracycline resistance gene in the pBR322 vector was not
experimentally modified, there would be no direct effect of codon bias change in the gene itself.
However, if the global translational selection hypothesis held true, the mut-8Leu-A mpR strain
would have decreased fitness in the presence of tetracycline because the cell would have a
reduced number of free ribosomes due to the back up of ribosomes that were translating the
mutated ampicillin gene.
The second experiment was a coevolution assay where the two genotype strains
competed in the same media. Equal amounts of WT and mut-8Leu-A mpR were added to the
same flask and grown for seven to ten days, with serial transfers every 24 hours, and cultures
plated every other day. To prevent cell strain bias from either REL606 or REL607, the
experiment was replicated with cell and genotype switched (see Figure 1). Following the
translational selection hypothesis, WT individuals were expected to grow faster, and thus be
more prevalent on the plate, than mut-8Leu-A mpR individuals. Though this experiment was only
carried out in ampicillin media, to test for global translational bias, it will need to be replicated in
the presence of tetracycline.
3
Methods
Creating mut-8Leu-A mpR cells
A manufacture mutated pBR322 ampicillin gene was created with mutations of seven of
eight preferred leucine codons changed to least preferred CTA codon triplet. Wild type pBR322
vectors were cut using AcuI to remove 755 base pairs of the 860 base pair ampicillin resistance
gene. The manufactured gene was subsequently spliced into wild type pBR322 vectors using
ligase. To mutate the final preferred leucine codon, mutagenesis was preformed using PfuUltra
HF DNA polymerase, creating a pBR322 ampicillin resistance gene with a total of 33
unpreferred leucine codons (mut-8Leu-A mpR ). E. coli REL606 and REL607 cells were
transformed using mut-8Leu-A mpR vectors and grown at 37°C on LB/ampicillin plates.
A ssessing Growth Rates
Wild-type pBR322 (WT) and mut-8Leu-A mpR -pBR322 cells were grown separately in
both LB/ampicillin (50µg/mL) liquid media and LB/tetracycline (20µg/mL) liquid media from
overnight starter cultures. Cells were grown at 37°C and shaken for eight hours. Optical Density
600 readings were taken every hour for
eight hours, using LB media as a zero.
Growth rates were averaged and
analyzed using a two-way analysis of
variance (ANOVA).
Competitive Growth
Cultures of equal amounts mut8Leu-A mpR -pBR322 and WT-pBR322
were grown in 10 mL of LB/ampicillin
liquid media. Genotypes were grown in
both REL606 and REL607 cells, with
the experiment performed in duplicate Figure 1. Average growth rates of E. coli strains at 37°C
so that the genotypes could be grown in with the WT gene as compared to the mutant gene. Growth
rates in the mutant strains are reduced compared to the WT
each cell type to avoid the presence of strain in the presence of 50µg/mL ampicillin, irrespective of
cell bias. Cultures were grown at 37°C host cell strain.
and 30°C for seven to ten days, with
serial transfers to new media occurring every 24 hours.
Two‐way ANOVA for Ampicillin
Cultures were plated on TA agar indicator plates to
Factor F P distinguish between the host cell strains. The number of
R
white and red cells were counted on each plate and analyzed Amp Genotype 9.532 0.015*
for each time point to determine growth rates for each Host cell strain 4.388 0.070
Interaction 0.570 0.472 genotype.
Results
A ssessing Growth Rates
OD600 measurements were used to determine the
growth rates of cultures in the presence of both ampicillin
and tetracycline separately. Growth rates were measured in
doublings per hour and compared between genotypes and cell
types. Box and whisker plots (Figures 1 and 2) were made for
Table 1. ANOVA analysis of
growth rates in the presence of
ampicillin. The presence of a
mut8Leu genotype produces a
significant disadvantage to growth.
However, strain of the host cell
does not produce a significant
advantage or disadvantage, and no
interaction was found.
4
each growth rate. Figure 1 shows that in the presence of
ampicillin, WT genotypes, in both REL606 and REL607,
had higher average growth rates than either strain
containing the mut-8Leu-A mpR genotype. In Table 1, the
two-way ANOVA analysis shows a significant difference
in growth rate, with a P value of 0.015, between WT and
mut8Leu genotypes, but not a significant difference
between host cell strains. This indicates that having a
mutant ampicillin resistance gene does negatively impact
growth in the presence of ampicillin, but cell type does
not produce a significant impact.
In
the
presence
of
tetracycline, however, significance
was not found for change in growth
rates based on genotype or cell type,
as shown in Table 2. Figure 2
indicates that WT-REL606 has a
higher average growth rate than
either
mut-8Leu-A mpR
strain.
However, WT-REL607 has a lower
average growth rate than either
mut8Leu strains.
Two‐way ANOVA for Tetracycline
Factor F P R
Amp Genotype 1.141 0.317
Host cell strain 0.047 0.833
Interaction 0.001 0.968 Table 2. ANOVA analysis of growth
rates in the presence of a tetracycline
media. In this media, genotype did not
produce a significant advantage or
disadvantage, and neither did host cell
strain.
Competitive Growth
Figure 2. Average growth rates of E. coli strains at 37°C with the
Frequencies of WT and mut- WT gene as compared to the mutant gene. Growth rates in the
8Leu-A mpR
genotypes
were mutant strains are reduced compared to the WT strain in the
averaged for each day of plating and presence of 20µg/mL tetracycline, irrespective of host cell strain.
compared across cell strains and
genotypes. As shown in table 4, frequencies of red cells (REL606) decrease over time, while
frequencies of white cells (REL607) increase whether they carry the WT or mut8Leu strain.
However, as shown in Figure 3,
white cells carrying the wild type
allele have a greater increased
frequency from day 0 than white
cells carrying the mut8Leu allele.
Table 3 shows this phenomenon in a
different way, showing that red
colonies carrying the mut8Leu allele
have a greater negative growth rate
than red colonies with the WT allele.
A t-test comparing the growth rates
of red colonies with the two
genotypes shows that this difference
is significant, thus indicating an Figure 3. Change in frequency of WT and mut8Leu white
important effect occurring with colonies were compared between day 0 and days 2, 7, and 9. WT
manipulating codon bias. Figure 4 cells always have a greater increased frequency change than
mut8Leu cells.
5
A verage Change in White Colony Frequency
Day 0 - 2
Day 0 - 7
Day 0 - 9
T-Test P
Between Plating
mut8Leu
0.085761489
0.078700519
0.082231004
0.008340277
WT
0.113309115
0.146690115
0.129999615
Table 3. Average change in white colony frequency from
day 0. Changes were calculated by subtracting the
frequency at day 0 from the frequency of the day in
question. Though all frequencies were increased from their
starting point, WT cells had a much greater positive
change in frequency than their mut-8Leu-AmpR
counterparts. A significant value of 0.008 was found when
comparing frequency changes.
also illustrates the change in frequency
associated with each genotype. Both white
strains on the graph have a positive slope,
indicating increased frequencies of white
colonies, while the frequency of red
colonies decreases as the experiment
progresses. It is important to note that the
slope of the line-of-best-fit of the WTwhite colonies is 0.0119, while the slope
of the mut8Leu colonies is only 0.0052.
Table 4 presents the average frequencies
for each cell strain and genotype over the
nine-day growth period.
Discussion
The changes in growth rates and
frequencies found between WT and mut8Leu-A mpR cells in both strains during
comparative as well as competitive
growth experiments suggests that codon
bias does in fact play a vital role in cell
Table 4. Frequencies of each genotype and cell strain on
efficiency during translation and thus
days they were plated. Frequencies of red cells decreased
effects the overall productivity of the cell.
from day 0, while frequencies of white cells increased.
The indication that a significant disHowever, WT white cells had a greater ending frequency
advantage was given to cells with the mutthan mut8Leu white cells.
8Leu-A mpR strain, as shown by Table 1,
signals a lower amount
of accurately translated
ampicillin
resistance
protein present in those
cells. This supports the
translational selection
hypothesis,
because
changing codons to
their least favored
counterparts decreased
the effectiveness of
those genes, seen in the
slower growth rates and
reduced frequency of
mut8Leu cells in both
Figure 4. Average frequency of WT and mutant strains in REL606 and REL607
experiments.
over 9 days. White (REL 607) always has an advantage, but it has more of an
Assessing the
advantage when it carries the WT genotype, as seen by the red squares which
have a line-of-best-fit slope of 0.0119, than when it carries the mutant gene,
growth rates of the WT
pictured by the “X” which have a line-of-best-fit slope of 0.0052. Both red strains
and mut8Leu geno(REL 606) have negative slopes for their line-of-best-fit, indicating a decreased
types in the two sepfrequency over the course of the experiment.
Frequency of Red and White Colonies
Day A Red A White- B RedB White
-WT
mut8Leu mut8Leu -WT
0
0.51
0.49
0.53
0.47
2
0.42
0.58
0.42
0.58
7
0.43
0.57
0.38
0.62
9
0.44
0.56
0.41
0.59
6
arate cell strains confirmed that WT cells grow significantly better than mut8Leu cells in the
presence of ampicillin. However, when the same experiment was carried out in the presence of
tetracycline, no significant effect was found from different genotypes. Though WT-REL606 did
have a higher average than either mut8Leu strains, WT-REL607 had a lower average growth rate
than the mut8Leu cells. The two-way ANOVA showed no significance associated with genotype,
indicating that the global translational selection hypothesis may not hold true. A decrease in cell
efficiency in the presence of tetracycline, with a mutant ampicillin resistance gene but a wild
type tetracycline resistance gene, would suggest that the free ribosomes of the cell are stuck on
the constitutively expressed ampicillin resistance gene, thus decreasing the amount of
tetracycline resistance that is expressed and diminishing the growth rate of the cell. However, as
WT cells did not have a significant advantage over mut8Leu cells, it cannot be concluded that
the global translational selection hypothesis is valid. This result may have been affected by the
concentration of tetracycline present in the growth media, as various concentration were tested
before selecting this one, many of which killed the cells. Perhaps replicating the test in the
presence of an array of tetracycline concentrations will provide a more comprehensive result and
provide some additional insight into the validity of the global translational selection hypothesis.
Competing WT and mut-8Leu-A mpR cells in the same media, however, did produce
significant results in terms of frequencies over time. Figure 3 shows the increased frequency of
WT white cells as compared to their mut8Leu counterparts, signifying that WT cells have a
growth advantage over those with less-preferred codons. Thus, when grown alongside each other,
cells with more preferred codons in the ampicillin resistance gene will appear more frequently
than cells with the mutated gene, indicating a faster growth and increased fitness for WT cells.
Figure 4 demonstrates that WT white cells continue to appear with increased frequency over
multiple days of growth, while the increase of white mutant cells occurs more slowly. As seen in
table 3, this difference is significant, with a P-value of 0.008, supporting the hypothesis that in a
competitive environment, cells with more frequently used codons will have a fitness advantage.
However, its important to note, as seen in Figure 4, that white cells, REL607, always
have an advantage over red cells, REL606. This is opposite of what is observed in the first
growth experiment, and the difference may be due to different growth temperatures, as cells in
the first experiment were grown at 37°C and cells in the competitive experiment were grown at
30°C. Nonetheless, when the two strains were grown at 37°C, as Tables 1 and 2 indicate, there
was not a significant difference found between the growth rates of the cell strains, and no
interaction was found. So though the frequency of white cells are greater for both genotypes in
the competitive growth experiment, this does not necessarily indicate the effect of a cell strain
advantage.
As has been seen in previous experiments testing for the effects of codon bias, the codons
present in the genes of a cell do have an impact on the translation of mRNA and thus the fitness
of the cell. As seen in both growth rate and competitive growth experiments, WT cells had an
advantage over mutant genotypes, indicating the benefit of having genes with preferred codons.
In this experiment, though only eight of 33 leucine codons were changed in the ampicillin
resistance gene of the transformed plasmid, eight mutations was enough to produce a notable
effect on cell fitness many generations after the mutation. Thus even a single codon may make a
difference in how a gene is translated and how a cell functions. This insight is important for
potential biomedical and biosynthetic applications in the future, and it will be imperative to not
only use the correct amino acid sequence in designing treatments, but the choice of individual
codons will also have a direct impact on the success of the therapy.
7
However, through this experiment, though support for the translational selection
hypothesis was uncovered no direct evidence was found, and the global translational selection
hypothesis could not be proven. Future experiments need to look into expression of RNA to
determine if the concentration of various tRNA in the cell are in fact the driving force behind
codon bias. Additionally, to gather more information about the global translational selection
hypothesis, various concentrations of tetracycline and different growth temperatures need to be
tested and assessed so that a standard and effective environment can be set up for cell growth
with reliable and consistent data.
Acknowledgements
The author would like to express her immense gratitude to Dr. David Carlini for all of his
help and support during this project, as well as to Annie Ballard for her company and for coming
into the lab on a Saturday. This work was supported in part by the Grebe Scholarship from
American University.
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