1. What techniques are used in the panel A,B C in figure 1?
2. What does the data show?
Transcribed Image Text: A
GFP
Phase
B
GFP
Phase
no gfp
no gfp
gfpwt
1:2
gfp
B
gfpns(TGA)
11544 | www.pnas.org/cgi/doi/10.1073/pnas.0912989107
containing two nonsense mutations within the gfp ORF (Fig. 14).
Moreover, fluorescence recovery after photobleaching experi-
ments showed that 35 min after bleaching, the fluorescent signal
displayed by the gfp mutant strains was almost restored to its
original level, confirming that the signal derived from de novo
inaccurate synthesis of protein molecules (SI Appendix, Fig. S1).
Importantly, a similar GFP expression pattern was observed for
mutations inserted into an endogenous B. subtilis gene (disA) fused
to gfp (SI Appendix, Fig. S2) (21), and in strains carrying identical
gfp alleles controlled by various promoters (SI Appendix, Fig. S3),
implying that errors occur constantly regardless of the tested allele
or the driving promoter.
We validated the formation of erroneous GFP molecules using
Western blot analysis (Fig. 1C). This examination revealed that full-
length GFP molecules are produced by the gfpfs and the gfpns alleles,
indicating that bypass of the mutations is carried out mainly at the
beginning of the ORF in the vicinity of the mutations. Evidently,
both fluorescent and immunoblot signals appeared to be stronger
for the gfpf strain than for gfpns (Fig. 1 A and C). This difference
most likely emanates from the possibility that nonsense mutation
can be read through specifically by erroneous introduction of an
amino acid at the stop codon, whereas the frame-shift mutation can
be bypassed by any compensatory frame-shift error at various sites
in the vicinity of the mutation. Of note, both mutations can be
bypassed by transcriptional or translational errors.
gfpis
gfp ns(TGA)
rpsL2
25
Kd-
gfpwt
gfpns(TAA) gfPnsX2(TAA,TGA)
Fig. 1. Observing errors in gene expression at a single cell level. (A) B. subtilis strains were grown to mid-exponential phase at 32 °C in hydrolyzed casein (CH)
medium supplemented with IPTG and observed by fluorescence microscopy. Fluorescence (Upper) and corresponding phase-contrast (Lower) images of the
following strains: PY79 (no gfp), SB444 (gfpwt), SB448 (gfpf), SB446 (gfpns(TAA)), and SB510 (gfpnsx2(TGA, TAA)). Fluorescence images have been normalized to
a similar intensity range, apart from the high-intensity image of SB444 strain, which was scaled down for presentation purpose. (Scale bar, 1 µm.) (B)
Fluorescence (Upper) and corresponding phase-contrast (Lower) images of the following strains: PY79 (no gfp), SB512 (gfpns (TGA)), SB632 (rpsL2, gfpns(TGA)),
SB608 (rpsD1, gfpns (TGA)), and SB616 (rpsD2, gfpns(TGA)). Cells were grown to mid-exponential phase at 32 °C in CH medium. Fluorescence images have been
normalized to a similar intensity range. (Scale bar, 1 µm.) (C) Immunoblot analysis of GFP protein extracts from strains: PY79 (no gfp), SB444 (gfpwt), SB448
(gfpfs), SB446 (gfpns(TAA)) grown at 32 °C to mid-exponential phase. Extracts were incubated with polyclonal anti-GFP antibodies. SB444 extract was diluted as
indicated, to serve as a reference for SB446 and SB448 extracts. Right panel was exposed for a longer period than left panel to detect low GFP amounts
(SI Appendix, SI Materials and Methods).
gfpns (TGA)
rpsD1
gfpns(TGA)
rpsD2
Next, we examined the strength and the consistency of our
system by replacing the original nonsense mutation (TAA) with
a TGA stop codon. TGA was shown to be decoded as tryptophan
at low efficiency in B. subtilis and thus to increase errors in protein
production (22). Accordingly, a strain carrying the gfPns (TGA) al-
lele displayed greater fluorescence than the one containing
the gfpns(TAA) allele (SI Appendix, Fig. S4). We then combined the
gfPns (TGA) allele with mutations in the genes encoding for the
RpsL and RpsD ribosomal proteins. Mutations perturbing RpsL
or RpsD activity are known to influence translational fidelity,
primarily by affecting the bypass of the TGA codon. Consistent
with previous observations (14), a mutation in rpsL that represses
translational errors decreased the fluorescence emanating from
the gfPns (TGA) strain. Conversely, mutations in rpsD that elevate
translational errors clearly increased the fluorescent signal ex-
hibited by the gfpns (TGA) strain (Fig. 1B).
All together, we established that under standard growth con-
ditions each bacterial cell spontaneously introduces errors during
gene expression to a significant level, which can be readily detected
using a mutant fluorescent gene.
Quantifying the Rate of Spontaneous Errors in Gene Expression. Next,
we estimated the average amount of errors that occur during ex-
ponential growth. The GFP signal emanating from the gfpfs and
gfPns mutant strains was quantified, averaged, and expressed as
a percentage of the GFP signal detected in gfpwt cells (Sİ Appendix,
Meyerovich et al.
PNAS
% fluorescence
E
0
GFP
22 27 32 37 42 [°C]
Phase
B
23°C
Meyerovich et al.
10
% fluorescence
09876
-Nw.
0
0.0
23°C
32°C
-37°C
-42°C
1.0
32°C
2.0 [OD]
25
25
Kd-
% protein
37°C
3.0
2.5
2.0
1.5
1.0
0.5
0.0
23
32
IS
SI Materials and Methods). Strikingly, the gfpf cells contained 2.4 ±
0.4% GFP molecules, whereas gfpns contained 0.4 ± 0.1%
fluorescent protein molecules relative to gfpwt cells. These values
were reproducible, and showed little variation among cells of each
strain. Importantly, estimates obtained from different promoters
driving the transcription of the mutant gfp alleles were similar, and
immunoblot signals from gfpfs and gfpns resembled that of gfpwt
diluted 1:50 and 1:200, respectively (Fig. 1C). These measure-
ments could even be underestimates, as mutations situated at the
beginning of an ORF are predicted to minimize the error level as
they predispose ribosomes to fall off the transcript (17, 23). To
further examine if the error rates detected are exceptional or re-
flect a more standard level, we measured the fluorescence ema-
nated from additional gfp mutated alleles. Replacing the
nucleotide causing the frame-shift mutation from A to G did not
affect the error level (SI Appendix, Fig. S4), suggesting that the
location rather than the sequence is critical for determining the
error level. Moreover, inserting frame-shift and nonsense muta-
tions into additional positions within the gfp ORF revealed similar
error frequencies (SI Appendix, Fig. S4).
A careful comparison of the values obtained using the gfpns
alleles (SI Appendix, Fig. S4) in B. subtilis with those obtained using
an ocher nonsense codon in E. coli (15, 17) revealed that our
measurements are at least 10-fold higher than previous estimates,
raising the possibility that an error occurs approximately once
every 200 codons. Errors exceeding 0.1% have been previously
reported for specific missense mutations and are generally con-
sidered exceptional (e.g. refs. 13 and 15). Our findings suggest that,
at least for B. subtilis, these values may represent a standard error
level, although the mechanisms for generating missense errors or
bypassing nonsense codons may differ (24). In addition, we show
that frame-shift errors are highly abundant, at least when located
at the beginning of the ORF (SI Appendix, Fig. S4). Thus, we
consider it likely that alternative translational products are pro-
duced frequently as a consequence of frame-shift errors. Taken
together, the error rates exhibited by the gfp mutant alleles support
the view that spontaneous errors have been underestimated.
37 42 [°C]
42°C
Fig. 2. Error level in gene expression is temperature de-
pendent. (A) Fluorescence levels (%) as a function of tempera-
ture in strain SB448 (gfps) grown to mid-exponential phase.
Fluorescence levels (%) are the average fluorescence signal of
strain SB448 (gfpfs) relative to the average fluorescence signal
of strain SB444 (gfpwt); both strains were grown to the same OD
and at the same temperature (SI Appendix, SI Materials and
Methods). (B) Fluorescence levels (%) as a function of OD, when
strain SB448 (gfps) was grown at different temperatures.
Fluorescence levels (%) were calculated as in A. (C) Immunoblot
analysis of GFP protein at different incubation temperatures.
Extracts from strains SB448 (gfpfs) (Upper), SB444 (gfpwt)
(Lower) grown at the indicated temperatures and PY79 grown
at 23 °C were incubated with polyclonal anti-GFP antibodies.
For SB444 only 1/20 of each extract was loaded (SI Appendix, SI
Materials and Methods). (D) Protein levels (%) as a function of
temperature in strain SB448 (gfps) as calculated from immu-
noblot analysis. Protein levels (%) are the calculated amount of
GFP protein from strain SB448 (gfps) relative to that of strain
SB444 (gfpwt); both strains were grown at the same tempera-
ture to the same OD 600 (SI Appendix, SI Materials and Methods).
(E) Fluorescence (Upper) and corresponding phase-contrast
(Lower) images of strain SB448 (gfpfs) grown to mid-exponen-
tial phase at the indicated temperatures. All fluorescence
images were normalized to a similar intensity range. (Scale bar,
1 μm.)
Error Levels in Gene Expression Are Dynamic. In view of our obser-
vations that errors are a prominent feature of bacterial gene ex-
pression, we reasoned that bacteria in natural habitats modulate
error rates. This theory led us to survey the effect of temperature
on the level of errors exhibited by B. subtilis cells, which naturally
reside in the soil. The gfpfs strain was used for this analysis be-
cause the GFP signal therein is higher than that of the gfpns strain,
allowing a greater range of variations to be detected. Samples of
gfpfis cells at mid-exponential phase grown at temperatures rang-
ing from 23 to 42 °C were collected and their fluorescent intensity
was compared with that displayed by gfpwt cells incubated at the
same temperatures (Fig. 2 A and E). We observed an inverse
correlation between temperature and error level, such that bac-
teria grown at the lowest temperature exhibited 70% more errors
than bacteria kept at the highest temperature, 3 ± 0.3 and 1.7 +
0.2%, respectively. Consistently, Western blot analysis showed
a similar correlation between the production of erroneous protein
molecules and temperature (Fig. 2 C and D). Importantly, no
significant difference was detected between the levels of wild-type
GFP molecules produced at the different temperatures, sug-
gesting that protein stability is not the cause for the observed
tendency. Thus, growth temperature has a direct effect on the
error level, implying that bacteria can modulate error rates in
nature. The reduced error level measured at higher temperatures
suggests that raising the temperature imposes the formation of
more accurate protein molecules.
Next, we tested whether there is any correlation between
growth phase and error level. A time-course experiment was
performed whereby the error levels were determined at different
growth phases at various temperatures. We found that the error
level correlates with optical density, reaching the highest values
at stationary phase during when the bacterium is challenged by
unfavorable conditions (Fig. 2B). These results were corroborated
by Western blot analysis showing a similar trend (SI Appendix,
Fig. S5). The error rates observed during stationary phase were at
least 2.1-fold higher than those observed during exponential phase
for all temperatures, with cells grown at the lowest temperature
reaching a mean level of more than 8% (Figs. 2B and 34). To rule
PNAS | June 22, 2010 | vol. 107 | no. 25 | 11545
MICROBIOLOGY