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Fill in the Table  Broad Topic: Specific Topic: What is known: Experimental Question:     Panel  Technique These data show: Figure 1 A B C

Fill in the Table  Broad Topic: Specific Topic: What is known: Experimental Question:     Panel  Technique These data show: Figure 1 A B C

Human Anatomy & Physiology (11th Edition)
Human Anatomy & Physiology (11th Edition)
11th Edition
ISBN:9780134580999
Author:Elaine N. Marieb, Katja N. Hoehn
Publisher:Elaine N. Marieb, Katja N. Hoehn
Chapter1: The Human Body: An Orientation
Section: Chapter Questions
Problem 1RQ: The correct sequence of levels forming the structural hierarchy is A. (a) organ, organ system,...
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Visualizing high error levels during gene expression in living bacterial cells Mor Meyerovich¹, Gideon Mamou¹, and Sigal Ben-Yehuda² Department of Microbiology and Molecular Genetics, Institute for Medical Research, Israel-Canada, Hebrew University-Hadassah Medical School, Hebrew University of Jerusalem, 91120 Jerusalem, Israel Edited* by Susan Gottesman, National Cancer Institute, Bethesda, MD, and approved May 20, 2010 (received for review November 19, 2009) To monitor inaccuracy in gene expression in living cells, we designed an experimental system in the bacterium Bacillus subtilis whereby spontaneous errors can be visualized and quantified at a single-cell level. Our strategy was to introduce mutations into a chromosomally encoded gfp allele, such that errors in protein production are reported in real time by the formation of fluorescent GFP molecules. The data reveal that the amount of errors can greatly exceed pre- vious estimates, and that the error rate increases dramatically at lower temperatures and during stationary phase. Furthermore, we demonstrate that when facing an antibiotic threat, an increase in error level is sufficient to allow survival of bacteria carrying a mu- tated antibiotic-resistance gene. We propose that bacterial gene expression is error prone, frequently yielding protein molecules that differ slightly from the sequence specified by their DNA, thus generating a cellular reservoir of nonidentical protein molecules. This variation may be a key factor in increasing bacterial fitness, expanding the capability of an isogenic population to face environ- mental challenges. Bacillus subtilis | translational errors | variations in living cells | translation fidelity NA is duplicated with remarkable fidelity to ensure that ac- information is from one generation to the next. This information is passed from DNA to RNA and from RNA to protein during gene expression; however, the ac- curacy of these downstream events is relatively less understood. Although RNA and proteins are generally considered short-lived noninherited molecules, several diseases are now known to arise from errors occurring during transcription and translation (1-3), implying that faithful transfer of genetic information from DNA to proteins is crucial for maintaining proper cellular functions. Interestingly, errors in gene expression can be beneficial, serving as a mechanism to promote noncanonical decoding. This strategy is mostly used by bacteria and viruses to increase diversity of partic- ular proteins and to express alternative translational products (4). In Escherichia coli for example, programmed translational frame- shifting in the dnaX gene produces DNA polymerase subunits with different enzymatic activities. The canonical product of dnaX confers extreme processivity on DNA polymerase, whereas the truncated protein expressed because of translational frame-shifting tempers the polymerase activity (5). In more general terms, errors arising spontaneously during gene expression may increase protein variety and thereby enable genetically identical cells to display heterogeneous phenotypes. This phenomenon is likely to contrib- ute to the robustness of unicellular organisms, allowing them to respond to fluctuating environments without changing their ge- notype (6-10). Errors in gene expression emanate from inaccuracies during the processes of transcription or translation. Transcriptional fidelity is determined largely by the capability of the RNA polymerase to sense and discriminate between cognate and noncognate pairing to the DNA template before incorporation of the next nucleotide (11). Faithful translation relies mainly on correct aminoacylation of a given tRNA, selection of the proper tRNA, and maintenance of the correct ORF throughout synthesis (12). In vivo measure- ments of errors in gene expression in bacteria have been estimated to occur at a rate of 104 to 10-5 per nucleotide during tran- scription and ≈10-3 to 10-4 per codon during translation. These error rates are significantly higher than that attributed to the high- fidelity replication process, where the frequency of errors is as low as 10-8 to 10-⁹ per nucleotide (8, 9, 12-20). For the most part, in vivo error rates in bacterial gene expression have been estimated by measuring the activity of a mutated re- porter gene (such as lacZ) (14, 17, 18) in a large cell population. However, the resultant measurements represent the average error rates, and thus do not detect the actual error level per cell and the variability, if any, among individuals. Moreover, these assays do not discriminate between errors in gene expression and genetic mutations. Here, we designed an experimental system to visualize and quantify the rate of spontaneous errors in gene expression at a single-cell level in living Bacillus subtilis cells. Our strategy was to introduce mutations into the ORF of a chromosomally encoded gfp reporter allele, such that errors in protein production would yield functional GFP molecules, visible by fluorescence micros- copy. Using this approach, we revealed that gene expression in bacteria is prone to high levels of errors reaching values that are much higher then eviously estimated. Moreover, we demon- strate that bacteria have the capability to modify error levels in response to physiological and environmental conditions. Results Visualizing Errors in Gene Expression. To visualize errors in gene expression at a single-cell level, we mutated a chromosomally encoded gfp reporter allele, such that errors in gene expression would generate functional GFP molecules. We reasoned that the use of highly sensitive fluorescence microscopy would enable us to detect small amounts of GFP molecules. Hence, we inserted frame-shift (gfps) or nonsense (gfpns) mutations at the beginning of the ORF of an inducible gfp gene. Ocher (TAA) was chosen as the nonsense mutation because it is the most abundant stop codon in the B. subtilis genome (SI Appendix). To monitor errors in gene expression arising during growth, cells bearing the different alleles were grown to mid-exponential phase and observed by fluorescence microscopy. As expected, a strong fluorescence signal was detected from cells expressing the wild- type gfp allele in the presence of the inducer (Fig. 14). Remarkably however, a clear fluorescent signal was also observed from strains bearing either the gfpfs or the gfpns alleles upon induction. In both strains, the signal appeared as a uniformly distributed weak cyto- plasmic haze present in all cells. This signal was above background level, as evidenced by the strain lacking the gfp gene or a strain Author contributions: M.M., G.M., and S.B.-Y. designed research, performed research, analyzed data, and wrote the paper. The authors declare no conflict of interest. *This Direct Submission article had a prearranged editor. ¹M.M. and G.M. contributed equally to this work. ²To whom correspondence should be addressed. E-mail: sigalb@ekmd.huji.ac.il. This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. 1073/pnas.0912989107/-/DCSupplemental.
Transcribed Image Text:Visualizing high error levels during gene expression in living bacterial cells Mor Meyerovich¹, Gideon Mamou¹, and Sigal Ben-Yehuda² Department of Microbiology and Molecular Genetics, Institute for Medical Research, Israel-Canada, Hebrew University-Hadassah Medical School, Hebrew University of Jerusalem, 91120 Jerusalem, Israel Edited* by Susan Gottesman, National Cancer Institute, Bethesda, MD, and approved May 20, 2010 (received for review November 19, 2009) To monitor inaccuracy in gene expression in living cells, we designed an experimental system in the bacterium Bacillus subtilis whereby spontaneous errors can be visualized and quantified at a single-cell level. Our strategy was to introduce mutations into a chromosomally encoded gfp allele, such that errors in protein production are reported in real time by the formation of fluorescent GFP molecules. The data reveal that the amount of errors can greatly exceed pre- vious estimates, and that the error rate increases dramatically at lower temperatures and during stationary phase. Furthermore, we demonstrate that when facing an antibiotic threat, an increase in error level is sufficient to allow survival of bacteria carrying a mu- tated antibiotic-resistance gene. We propose that bacterial gene expression is error prone, frequently yielding protein molecules that differ slightly from the sequence specified by their DNA, thus generating a cellular reservoir of nonidentical protein molecules. This variation may be a key factor in increasing bacterial fitness, expanding the capability of an isogenic population to face environ- mental challenges. Bacillus subtilis | translational errors | variations in living cells | translation fidelity NA is duplicated with remarkable fidelity to ensure that ac- information is from one generation to the next. This information is passed from DNA to RNA and from RNA to protein during gene expression; however, the ac- curacy of these downstream events is relatively less understood. Although RNA and proteins are generally considered short-lived noninherited molecules, several diseases are now known to arise from errors occurring during transcription and translation (1-3), implying that faithful transfer of genetic information from DNA to proteins is crucial for maintaining proper cellular functions. Interestingly, errors in gene expression can be beneficial, serving as a mechanism to promote noncanonical decoding. This strategy is mostly used by bacteria and viruses to increase diversity of partic- ular proteins and to express alternative translational products (4). In Escherichia coli for example, programmed translational frame- shifting in the dnaX gene produces DNA polymerase subunits with different enzymatic activities. The canonical product of dnaX confers extreme processivity on DNA polymerase, whereas the truncated protein expressed because of translational frame-shifting tempers the polymerase activity (5). In more general terms, errors arising spontaneously during gene expression may increase protein variety and thereby enable genetically identical cells to display heterogeneous phenotypes. This phenomenon is likely to contrib- ute to the robustness of unicellular organisms, allowing them to respond to fluctuating environments without changing their ge- notype (6-10). Errors in gene expression emanate from inaccuracies during the processes of transcription or translation. Transcriptional fidelity is determined largely by the capability of the RNA polymerase to sense and discriminate between cognate and noncognate pairing to the DNA template before incorporation of the next nucleotide (11). Faithful translation relies mainly on correct aminoacylation of a given tRNA, selection of the proper tRNA, and maintenance of the correct ORF throughout synthesis (12). In vivo measure- ments of errors in gene expression in bacteria have been estimated to occur at a rate of 104 to 10-5 per nucleotide during tran- scription and ≈10-3 to 10-4 per codon during translation. These error rates are significantly higher than that attributed to the high- fidelity replication process, where the frequency of errors is as low as 10-8 to 10-⁹ per nucleotide (8, 9, 12-20). For the most part, in vivo error rates in bacterial gene expression have been estimated by measuring the activity of a mutated re- porter gene (such as lacZ) (14, 17, 18) in a large cell population. However, the resultant measurements represent the average error rates, and thus do not detect the actual error level per cell and the variability, if any, among individuals. Moreover, these assays do not discriminate between errors in gene expression and genetic mutations. Here, we designed an experimental system to visualize and quantify the rate of spontaneous errors in gene expression at a single-cell level in living Bacillus subtilis cells. Our strategy was to introduce mutations into the ORF of a chromosomally encoded gfp reporter allele, such that errors in protein production would yield functional GFP molecules, visible by fluorescence micros- copy. Using this approach, we revealed that gene expression in bacteria is prone to high levels of errors reaching values that are much higher then eviously estimated. Moreover, we demon- strate that bacteria have the capability to modify error levels in response to physiological and environmental conditions. Results Visualizing Errors in Gene Expression. To visualize errors in gene expression at a single-cell level, we mutated a chromosomally encoded gfp reporter allele, such that errors in gene expression would generate functional GFP molecules. We reasoned that the use of highly sensitive fluorescence microscopy would enable us to detect small amounts of GFP molecules. Hence, we inserted frame-shift (gfps) or nonsense (gfpns) mutations at the beginning of the ORF of an inducible gfp gene. Ocher (TAA) was chosen as the nonsense mutation because it is the most abundant stop codon in the B. subtilis genome (SI Appendix). To monitor errors in gene expression arising during growth, cells bearing the different alleles were grown to mid-exponential phase and observed by fluorescence microscopy. As expected, a strong fluorescence signal was detected from cells expressing the wild- type gfp allele in the presence of the inducer (Fig. 14). Remarkably however, a clear fluorescent signal was also observed from strains bearing either the gfpfs or the gfpns alleles upon induction. In both strains, the signal appeared as a uniformly distributed weak cyto- plasmic haze present in all cells. This signal was above background level, as evidenced by the strain lacking the gfp gene or a strain Author contributions: M.M., G.M., and S.B.-Y. designed research, performed research, analyzed data, and wrote the paper. The authors declare no conflict of interest. *This Direct Submission article had a prearranged editor. ¹M.M. and G.M. contributed equally to this work. ²To whom correspondence should be addressed. E-mail: sigalb@ekmd.huji.ac.il. This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. 1073/pnas.0912989107/-/DCSupplemental.
A GFP Phase B GFP Phase C 25 no gfp no gfp gfpwt gfp ㅂ gfp ns(TGA) ge gfpns (TGA) rpsD1 gfpts 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. gfPns(TGA) rpsL2 25 Kd- gfpns(TAA) gfpnsX2(TAA,TGA) gfpwt 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 (gfps), SB446 (gfpns(TAA), and SB510 (gfp nsx2(TGA, TAA)). Fluorescence images have been normalized to 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 incu 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). gfp ns(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 gfps(TGA) al- lele displayed greater fluorescence than the one containing the gfPns (TAA) allele (SI Appendix, Fig. S4). We then combined the 8fPns (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 (SI Appendix, PNAS PNAS PNAS A % fluorescence E FA GFP 22 27 32 37 42 [°C] B 23°C Phase 6 fluorescence AGSL860 10 9 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 Zl SI Materials and Methods). Strikingly, the gfp 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 (gfpfs) 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 ials and Methods). (D) Protein levels (%) as a function 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 gfpfs 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
Transcribed Image Text:A GFP Phase B GFP Phase C 25 no gfp no gfp gfpwt gfp ㅂ gfp ns(TGA) ge gfpns (TGA) rpsD1 gfpts 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. gfPns(TGA) rpsL2 25 Kd- gfpns(TAA) gfpnsX2(TAA,TGA) gfpwt 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 (gfps), SB446 (gfpns(TAA), and SB510 (gfp nsx2(TGA, TAA)). Fluorescence images have been normalized to 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 incu 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). gfp ns(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 gfps(TGA) al- lele displayed greater fluorescence than the one containing the gfPns (TAA) allele (SI Appendix, Fig. S4). We then combined the 8fPns (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 (SI Appendix, PNAS PNAS PNAS A % fluorescence E FA GFP 22 27 32 37 42 [°C] B 23°C Phase 6 fluorescence AGSL860 10 9 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 Zl SI Materials and Methods). Strikingly, the gfp 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 (gfpfs) 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 ials and Methods). (D) Protein levels (%) as a function 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 gfpfs 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
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