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Slowing translation between protein domains by increasing affinity between mRNAs and the ribosomal anti-Shine-Dalgarno sequence improves solubility Kevin Andres Vasquez, Taylor A Hatridge, Nicholas C Curtis, and Lydia Contreras ACS Synth. Biol., Just Accepted Manuscript • DOI: 10.1021/acssynbio.5b00193 • Publication Date (Web): 25 Nov 2015 Downloaded from http://pubs.acs.org on November 30, 2015

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ACS Synthetic Biology

Slowing translation between protein domains by increasing affinity between mRNAs and the ribosomal anti-Shine-Dalgarno sequence improves solubility Kevin A. Vasquez, Taylor A. Hatridge, Nicholas C. Curtis, and Lydia M. Contreras*

Abstract Recent studies have demonstrated that effective protein production requires coordination of multiple cotranslational cellular processes, which are heavily affected by translation timing. Until recently, protein engineering has focused on codon optimization to maximize protein production rates, mostly considering the effect of tRNA abundance. However, as it relates to complex multi-domain proteins, it has been hypothesized that strategic translational pauses between domains and between distinct individual structural motifs can prevent interactions between nascent chain fragments that generate kinetically-trapped misfolded peptides and thereby enhance protein yields. In this study, we introduce synthetic transient pauses between structural domains in a heterologous model protein based on designed patterns of affinity between the mRNA and the anti-Shine-Dalgarno (aSD) sequence on the ribosome. We demonstrate that optimizing translation attenuation at domain boundaries can predictably affect solubility patterns in bacteria. Exploration of the affinity space showed that modifying less than 1% of the nucleotides (on a small 12 amino acid linker) can vary soluble protein yields up to ~7fold, without altering the primary sequence of the protein. In the context of longer linkers, where a larger number of distinct structural motifs can fold outside the ribosome, optimal synonymous codon variations resulted in an additional 2.1 fold increase in solubility, relative to nonoptimized linkers of the same length. While rational construction of 54 linkers of various affinities showed a significant correlation between protein solubility and predicted affinity, only weaker correlations were observed between tRNA abundance and protein solubility. We also demonstrate that naturally occurring high-affinity clusters are present between structural domains of β-galactosidase, one of E. coli’s largest native proteins. Inter-domain ribosomal affinity is an important factor that has not previously been explored in the context of protein engineering.

Keywords protein folding, translation timing, synonymous codons, silent mutations, ribosome pausing

Introduction Protein synthesis involves coordination of many concomitant cellular processes, many of which are carried on by ribosomes themselves. Indeed, in addition to their central role in protein biosynthesis, cellular ribosomes have been linked to protein folding, secretion regulation, targeting, and translation regulation [1-4]. This is not surprising given that a nascent protein

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translocates within the ribosome through an exit tunnel that can accomodate 30-72 amino acids [5]. As such, most nascent proteins achieve high exposure to cellular factors before the full protein is synthesized. These cotranslational processes take place prior to the full synthesis of a protein and involve: interactions with molecular chaperones, translocation between cellular compartments, formation of a stable tertiary stucture, glycosylation, and ubiquitination [6]. Several lines of evidence support the existence of co-translational mechanisms, including: the demonstration that proteins can display their enzymatic activity immediately upon their release from the ribosome (a much smaller timescale than if posttranslational folding were required); the ability of growing polypeptides to bind specific ligands or cofactors while bound to the ribosome; and the occurrence of limited proteolysis prior to synthesis of the full-length protein [7,8]. It can therefore be expected that controlling protein synthesis may lead to altered properties of a newly synthesized protein. An interesting observation is that translation rates in higher organisms (e.g. yeast; ~5-9 amino acids per second (aa/sec)) [2] are slower than in E. coli (~12-21 aa/sec) [9]. Given that 65% of proteins encoded by eukaryotes have been predicted to contain two or more domains (compared to 40% in bacteria [10]) and to encode for an increased number of structurally complex proteins that contain distinct structural motifs, slowing translation could benefit the processing of more complex proteins [8, 11-14]. Because the number of conformations accessible to a polypeptide chain grows exponentially with chain length, computational models predict that slowing the rate of amino acid chain extrusion could lead to a more favorable distribution of appropriately folded polypeptide chains [15]. This has been demonstrated experimentally by increased proteolysis when translation attenuation sites were depleted [16] and by enhanced folding when global translation rate is decreased by changing culture temperature and streptomycin concentrations [16, 17]. Furthermore, incorporating low abundance tRNA codons in domain boundaries enhanced protein yields, demonstrating that synthetic translation attenuation sites can be engineered to improve solubility [18]. A recent study has expanded and formalized a codon optimization strategy for heterologous protein expression that was applied to a large protein collection (100 human proteins) for production in E. coli [19]. This optimization scheme aimed to simultaneously optimize high tRNA availability codons and G-C content while decreasing DNA cleavage sites and mRNA secondary structure. Although this notion of codon optimization was not aimed to directly affect the synthesis pace of the ribosome, this strategy was successful at increasing total translated protein yields. However, it is worth mentioning that about 20% of the sequences calculated from this algorithm resulted in decreased total expression, suggesting that other underlying factors influence protein production efficiency. More recently, advances in DNA-sequencing capabilities have allowed sophisticated genome-wide profiling of ribosome’s locations [20]. Insights from this work are beneficial in understanding how the nucleotide code calls for translational pausing of ribosomes. A major unexpected finding from this work is that low abundance tRNA codons do not correlate well with sites where ribosomes are slowed (particularly in nutrient-rich media), while sites that resemble the Shine-Dalgarno sequence demonstrate increased ribosomal occupancy. This suggests that Shine-Dalgarno-like sequences often function as ribosomal pausing sites.


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In this study, we propose the hypothesis that positioning Shine-Dalgarno-like sequences as strategic translation attenuation sites leads to enhanced protein yields by improving cotranslational processing of distinct structural domains. We have tested this hypothesis using a model two-domain protein chimera (involving Pyrobaculum aerophilum 3-hexulose 6-phosphate synthase, H6P, and the Green Fluorescence Protein, GFP): H6P-GFP. This model protein has been previously characterized to exhibit relatively poor solubility in E. coli due to its complex architecture, likely involving multiple folding motifs [21]. Specifically, we explored the effect of the affinity between the interdomain region of the mRNA (i.e. the linker-coding region, LCR) and the anti-Shine-Dalgarno (aSD) sequence of the ribosome on the solubility of H6P-GFP. Initially, we screened a random library of LCR sequences containing synonymous codon mutations to confirm the ability of these mutations to affect protein solubility. Additionally, we synthesized a rational library of 54 mutants that, at the mRNA level, exhibited a range of affinities to ribosomes without changing the primary protein sequence. In general, our work demonstrates that synonymous codon mutations to a small linker region that lead to affinity increases can be significantly correlated to improvements in protein solubility (R = 0.439, p = 0.000795). We later demonstrate that further enhancements to protein solubility are attainable by increasing linker length such that translation attenuation occurs after the entire H6P domain has exited the ribosome. A variety of natural stalling peptide sequences have been uncovered throughout bacteria to regulate other co-translational processes, like secretion [22]. These translational timing schemes have already been highly exploited in biotechnology applications [23-25]. The presence of these naturally occurring translation attenuation peptides motivated our exploration of native linkerlike sequences that could have evolved within interdomain regions in complex proteins to promote better protein solubility, perhaps by differential affinity to the aSD sequence. To understand the interplay between ribosomal affinity profiles and complex protein solubility, we characterized the affinity of large unstructured regions in β-galactosidase (β-gal). β-gal is a particularly large, naturally occurring protein in E. coli, whose structure has been thoroughly characterized and can provide the ability to explore codon choice, affinity, and their potential effects on translational timing and solubility. In this study we found that, within this naturally occurring protein, high-affinity domain clusters appear to have evolved between structural elements (in linker-like regions). Importantly, in this work we characterize a correlation between mRNA-aSD affinity and protein solubility that, to our knowledge, has not been explicitly explored as a protein engineering strategy.

Results and Discussion Establishing a model multidomain protein system that can display changes in solubility via synonymous codon mutations within the linker-coding region To validate that synonymous substitutions can alter the solubility of the H6P-GFP model protein, we randomly modified the 24-nucleotide sequence within the linker between H6P and GFP, as shown in Figure 1A. Our selection of this model protein was driven by our ability to assay its solubility in a rapid and high-throughput way, as measured by changes in fluorescence. Furthermore, the H6P-GFP chimera has been characterized to have intermediate solubility relative to other GFP fusions [21].


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Initially, we constructed a linker library with a theoretical diversity of (4)8 = 65,536 variants using synthetic degenerate oligonucleotides to randomize the third position of the codons within the linker region. After sorting this library, we isolated 400 mutants that displayed at least a twofold increase in fluorescence relative to the non-mutated wild-type (wt) H6P-GFP sequence. Following confirmation of gain-in-fluorescence of the isolated colonies on 96-well plates, we selected the 20 most fluorescent mutants for sequencing. Among this set of most fluorescent clones, the five mutants (R1-R5) that were unique (and that did not have deleterious mutations) were selected for future characterization. Sequencing confirmed that these mutants have synonymous coding sequences to the wt H6P-GFP. Figure 1B summarizes the library construction and screening scheme. Upon detailed characterization, representative data illustrated in Figure 1C, we found that these clones exhibited up to a 1.4-fold increase in average median fluorescence relative to the wt sequence. As shown in Figure 1D, higher yields of the H6P-GFP protein were confirmed by Western blotting analysis of the soluble fraction of all mutants that exhibited higher fluorescence relative to wt H6P-GFP. It is worth noting that we observed no difference in the levels of total protein synthesized (Supplementary Figure 1), as measured by Coomassie staining analysis of total protein lysate. Given that the inherent protein instability (quantified by the presence of both an H6P-GFP band and an unfused GFP band) may vary as a function of linker sequence, we examined levels of both H6P-GFP and GFP. In the case of the R1-R5 linker mutants, relative differences between GFP and the fusion protein were determined to be insignificant by quantitative Western blotting analysis. Changes in solubility due to random synonymous mutations correlate with changes in affinity between the ribosomal aSD sequence and the mRNA linker-coding region After validating the possibility of inducing quantitative solubility changes to the H6P-GFP model protein by synonymous codon modifications of its linker region, we next characterized the effects of these mutations. After sequencing clones R1-R5, we demonstrated that no mutation affected the primary sequence of the H6P-GFP fusion (Figure 2A). Importantly, after calculating the affinity of the LCR’s in mutants R1-R5 to the aSD sequence, we observed a strong positive correlation (R = 0.986, p = 0.000307) between predicted affinity and protein solubility, as measured by fluorescence (Figure 2B). Although this was a small sample of mutants, these results were particularly encouraging in demonstrating that increases in affinity between the aSD sequence and the LCR could improve soluble protein yields. In this context, modification to a maximum of 1.65% of codons (8 out of a total 485) exhibited up to a 5-fold increase in protein solubility, as measured by quantification of Western blots. Notably, Western blotting analysis points towards a more pronounced increase in protein solubility relative to fluorescence measurements. The difference can be attributed to protein instability, which cannot be accounted for directly in fluorescence measurements, but can be directly detected through Western analysis. For this reason, Western quantification likely provides a more accurate report on protein folding. Due to the high-throughput nature of fluorescence measurements we performed our initial screen using fluorescence and proceed in all cases with Western blotting analysis to validate and better quantitate relative values obtained by our fluorescence screen. Importantly, the relative trends between all mutants were consistent between these two analyses. The scheme used to predict affinities between the aSD sequence on the ribosome and each LCR is outlined in Figure 2C. As described in the methods, NUPACK [26] was used to compute the energy of interaction between each mutant LCR and the aSD sequence. Similar to analysis


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performed in Li et al.’s study [20], we used the lowest possible hybridization energy (kcal/mol) for the mRNA interacting with the eight nucleotide canonical aSD sequence, 5′-CACCUCCU-3′. The affinities were calculated using a sliding window that computed the affinity for each codon pair (6-mer) of the LCR, tabulated as Ni x Nj matrices (included as Supplementary Table 1). The overall affinity was calculated as the sum of each codon pair’s affinity. By designing affinity, linkers that contained synonymous codon sequences that in their affinity level (low, medium, or high) were relatively similar, capturing the overall linker affinity by a summation scheme did not represent a strong bias towards any particularly strong codon pair. Because there is no change in LCR length, the addition is also self-normalizing. For convenience, and due to the fact that the ribosome never interacts with the entire linker sequence at one point, a relative predicted affinity was calculated as the ratio of the mutant affinity to the wt sequence affinity. Using previously reported values [27], we calculated the tRNA abundance for each LCR. Relative tRNA abundance was again calculated as a ratio between the mutant abundance and wt sequence abundance. Although our initial results showed a positive correlation between protein solubility and aSD affinity, we were not able to correlate protein solubility linearly with tRNA abundance (p = 0.804) (Figure 2D). We attribute this to the small number of samples.. Rational design of a large linker library that exhibits a wide range of aSD affinities Given our initial observations that mRNA-aSD affinity could be a strong predictor of protein solubility, we wanted to validate this observation with a larger set of rationally designed constructs. Based on our analysis of the five initial mutants, we predicted that increasing affinity should lead to increased solubility. To test this prediction, we constructed a set of 54 additional H6P-GFP mutants, where the mRNA-aSD affinity was rationally modified via synonymous mutations, as predicted by our calculations (outlined in Figure 2C). For a wider exploration of the effect of aSD affinity on protein solubility, we designed three major linker groups that contrasted strongly in their relative affinity (low (L), medium (M), and high (H)). As shown in Figure 3A, our synonymous codon library consisted of 28 low, 18 medium, and 14 high affinity H6P-GFP LCR clones. Total affinity values are summarized in this figure, with units of kcal/mol. For reference, the affinity of the wt and the R1-R5 sequences falls within the designed low and medium affinity groups, respectively. Given that all linker-encoding regions are designed to maintain identical protein primary sequence, we had natural constraints in the total number of mutants that we could generate in each of these categories; we did not generate every possible construct, just a representative span of predicted affinities. Figure 3B displays the distribution of predicted affinities for the mutants that were generated. Affinity between aSD sequence and mRNA is a good predictor of multidomain protein solubility As shown by our characterization of the additional 54 linker coding region mutants, we observed a positive correlation between predicted mRNA-aSD affinities and solubility (Figure 4A). For this analysis, affinity was calculated with the scheme illustrated in Figure 2C and solubility was assayed by fluorescence measurements using flow cytometry. It is worth noting that changes in solubility of all the mutants relative to the wt linker reported by fluocytometry (Figure 4A) are consistent with the trends observed by Western blotting analysis (Supplementary Figure 2). In agreement with our hypothesis, the significant correlation of 0.439 (p-value of .000795) demonstrates that protein solubility is enhanced by increasing mRNA-aSD affinity. It is also worth noting that in the case of this rationally constructed library, we saw a slightly weaker and


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inverse correlation between tRNA abundance and solubility (R = -.378, p = .00286), as shown in Figure 4B. This result differs from expectations based on traditional codon optimization but is consistent with recent literature reports that exploit the incorporation of less abundant codons to improve protein solubility [12,15-18]; highlighting that optimization of translation timing into the host organism goes steps beyond maximizing host codon usage for optimization of protein production.

Effect of a longer high-affinity linker on protein solubility Up to this point, our work focused on testing the effect of engineering affinity on one 12 AA linker unit, a typical length used to express complex multi-domain proteins. As presented so far, our efforts to explore the correlation between (linker-aSD) affinity and solubility fully explored the convenient sequence space of this linker length. In this case, linker design was optimized for examining solubility enhancements that occur by formation of local distinctive structural features (like alpha helices) that would promote overall protein folding within an entire protein domain. To explore if a rationally designed high-affinity linker would be equally effective for enhancing the solubility of a two-domain protein, once the first domain (in this case H6P) was presumably completely released from the ribosome, we designed five variations of a longer linker sequence where each linker consisted of a total of 8 repeats of combined wild-type and/or H13 linkers, (wt-H13)8; these five constructs represent the following compositions: wt8, wt7H131, wt6H132, wt3H135, H138 (schematic in Figure 5A). The H13 linker was selected as it produced the largest increase in protein solubility and was predicted as the second highest affinity linker. As measured by Western analysis, even with a single copy linker H13 achieved a 6.9- fold change in solubility relative to wt. It is worthwhile noting that this rationally designed linker provided further protein solubility increases relative than the 5-fold increase in solubility observed by the best randomly generated linker (R5). In designing repeats of high affinity linkers, our rationale was to systematically increase the number of instances in which translation attenuation could occur relative to the wt linker. Importantly, it is known that the ribosomal exit tunnel can accommodate ~ 30-72 amino acids [5] and therefore, a linker consisting of 68 amino acid residues likely guarantees exit of the entire H6P domain for co-translational folding prior to the release of the second GFP domain. This linker length has been previously demonstrated to lead to full co-translational protein display out of the ribosome [24]. As reported in earlier works [29] the length of the linker itself led to a major increase in solubility; this is evidenced by the observed 26-fold increase of the H6P-GFP when 8 copies of the wt linker (wt8) instead of a single copy (Figures 5B and 5C) were used. Importantly, an additional 2.1-fold increase in solubility was achieved when 8 copies of the H13 linker were used (H138), instead of 8 copies of the wt linker (wt8). Combined, the effect of translation attenuation and increased linker length led to a total 53-fold increase in protein solubility (H6P-GFP). Analysis of naturally occurring multi-domain protein shows that linker regions separating highly structured domains have higher codon affinities to the anti-Shine-Dalgarno sequence. Based on our results, we hypothesized that linker regions of native proteins may strategically function as translation attenuation sites between structural elements. To evaluate the possibility that naturally occurring linker regions could be encoded by codon pairs that display higher


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affinity, we used β-galactosidase (β-gal) as a model protein. The structure of β-gal, a large 1,023 amino acid polypeptide chain, has been thoroughly characterized and is known to form many secondary structures in 6 discrete domains: an α-complementation region at the N-terminus, D1, D2, D3, D4, and D5 [28]. Importantly, due to its highly complex structure, it has been hypothesized that β-gal folding requires sophisticated translational timing and cotranslational folding control [14]. For our codon affinity analysis, the natural β-gal amino acid sequence and its structural element distribution was obtained from previous crystallography work [28] and its natural coding sequence was obtained from E. coli strain K-12 MG1655 (c366305-363231) from NCBI [NC_000913.3]. Using this information, we compared the relative aSD affinities of synonymous codon pairs in unstructured linker regions to highly structured regions (α-helices and β-sheets). We analyzed the ribosomal affinity of the three largest unstructured linker-like regions between structural elements. These linker regions (Linkers 1, 2, and 3) are represented by amino acids 1838, 102-119, and 486-519, respectively. Figure 6 outlines the scheme to characterize linker regions and calculates the affinity of codon pairs in Linkers 1, 2 and 3 and the structured regions. Briefly, in this analysis we evaluated the mRNA-aSD affinities of all 6-nucleotides encoding for specific amino acid pairs within the linker region of interest using NUPACK [26] (as described in Figure 2C). We then identified all other occurrences of each amino acid pair in the structured regions of the protein and compared the predicted affinities across these different regions. Complete data for this analysis is included as Supplementary Table 2. Our analysis covered 263 codon pairs, representing ~25% of the protein sequence. Predicted affinity values as well as the relative predicted affinity in the linker to structured regions are shown in Figure 7. For Linker 1, the naturally occurring codon pairs were observed to display equal or lower affinity to the aSD sequence relative to other synonymous codon pairs encoding for the same amino acids in all other structured regions of the protein. However, codon pairs that encode for Linkers 2 and 3 displayed, on average, higher affinity relative to synonymous codon pairs encoding the same amino acids in structured regions of the protein. This analysis suggests that in natural, multidomain proteins synonymous codon pairs within unstructured domains could display higher affinity than their counterparts in structured domains. Interestingly, this trend was only observed in Linkers 2 and 3, which represent protein sequences past a critical point in translation (after synthesis of ~30-72 amino acids), where at least a fraction of the protein is presumed to have exited the ribosome and is available for cotranslational processing [5]. Further analysis of β-gal or other large naturally occurring proteins could be helpful in understanding the effect of affinity and position for different codon pairs. Conclusions This work highlights the possibility of rationally engineering synonymous codons in a way that optimizes affinity to favorably affect protein solubility, without the need for random screens. The effective coordination of cotranslational protein processing has become increasingly relevant to protein engineering. In particular, coordinating translational pausing in domain boundaries to reduce high-energy, inter-domain interactions is believed to optimize productive peptide folding [16, 18, 19]. In this work, we explore the hypothesis that translation attenuation can be engineered to increase protein yields of complex, multidomain proteins by modulating the affinity between an mRNA and the anti-Shine-Dalgarno sequence of the ribosome. Given earlier


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work describing the interactions between the aSD sequence of the 16S ribosomal RNA and an mRNA as a major determinant of transient translation pausing [20], we reasoned that it was highly possible that changes in the mRNA-aSD affinities could induce brief pauses in translation. This would allow for nascent chain rearrangements on a time-scale smaller than peptide generation, thus limiting kinetically trapped, misfolded protein states. Particularly, in the case of complex multidomain proteins, extrusion of amino acids in an upstream domain followed by a decrease in translation rate (during synthesis of an interdomain linker region) may lead to favorable nucleation of structural elements that lead to correct folding. This occurs sequentially and independently from the nucleation of other C-terminal domains. In contrast, at the limit of uniformly fast translation (for all protein domains), folding nucleation is more likely to occur between amino acids that make up different domains, increasing the generation of incorrect secondary and tertiary contacts. A mechanistic depiction of these notions is depicted in Figure 8. As we have demonstrated, a complex interplay exists between maximizing translational output and effective synthesis of functional proteins. That is, maximizing total protein synthesis by fast translation kinetics (i.e. by usage of the most abundant or weakest aSD affinity codons) may compromise cotranslational folding. More studies in this area will continue to highlight systematic ways that enable full exploitation of translational timing, using tools such as mRNAaSD affinities for protein engineering.

Materials and Methods Plasmid and Bacterial Strains The plasmid construct pET-H6P-GFP, used to encode the model protein in our studies, was kindly gifted to our lab by the Waldo lab. The construct was used as previously constructed and characterized in previous work [21]. This plasmid was used for the generation of our random and rational mutation libraries. Escherichia coli BL21 (DE3) cells were used for all expression experiments. The H6P-GFP construct consists of a fusion between the Pyrobaculum aerophilum 3-hexulose 6-phosphate synthase (H6P) and the Green Fluorescence Protein (GFP), where appropriate folding of the downstream protein (GFP), measured by fluorescence, acts as a reporter for the solubility of the upstream H6P. Construction of the random linker coding region library To construct a random library of LCR regions with varying ribosomal affinities, we targeted 8 codons at the center of the 12 amino acid linker region. The targeted region was flanked by BamHI and EcoRI restriction sites within the plasmid construct (Figure 1A). Specifically, we performed a PCR amplification of the H6P gene with the following degenerate synthetic oligonucleotides that hybridized to the 5’end of the H6P gene and the 3’end of the linker sequence: forward primer IDT686 (5’-3’) (GAT ATA CCA TGG GCA GCA GCC ATC ATC ATC) and reverse primer IDT685 (5’-3’) (TTT GCT GAA TTC NCC NGA NCC NGC NGC NGA NCC NGC GGA TCC GAT ATG TTT TAA AAT GTT GTT CAT CAT CAT TAC A). In this design, the degenerate reverse primer randomly altered the third position in the middle eight codons of the sequence coding for the linker. This design accommodated for the use of the degeneracy in the glycine, serine, and alanine, as each is encoded by codons with a four-fold degenerate third position (serine is encoded by an additional pair of codons, AGU and AGC, with two-fold degeneracy, but for simplicity these codons were not utilized). After obtaining


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these PCR amplified fragments these were gel-purified from a 1% TAE-agarose gel using the Illustra GFX PCR DNA and Gel Band Purification Kit (GE Healthcare) and digested using NcoI and EcoRI. These fragments were ligated with NcoI/EcoRI-digested pET-H6P-GFP. Screening of Random Linker Coding Region Library We performed all library screenings in BL21 (DE3) cells. We isolated cells that exhibited gainof-fluorescence relative to the wild-type cells (expressing the wild-type H6P-GFP protein). Screens were performed as previously reported [30]. Briefly, successfully transformants carrying pET-H6P-GFP were recovered from plates by adding 1 mL of sterile Difco Luria Broth (LB) (Benton-Dickinson (BD) Company). Sterile plastic scrubbers were used to resuspend cell colonies. Once discrete colonies could not be seen on the agar, the slurry was transferred to the next agar plate to minimize the culture volume necessary. After all colonies were collected, the slurry was diluted 1:10 into fresh, sterile LB. After 1 hour recovery, 900 µL of culture media were combined with 900 µL of 40% glycerol and frozen at -80°C. These frozen aliquots were used to inoculate 40 mL of LB. Culturing was performed at 37°C to an OD600 of ~0.6-0.8 (approximately 4 hours). At this point, the culture media containing the library was split into two flasks, and half of the media was induced with isopropyl-β-D-thiogalactopyranoside (IPTG) (final concentration 1mM). After five hours of protein expression, 100 µL of media was collected from each flask, spun down for three minutes in a table-top Ependorf 5424 at a maximum speed of 15,000 rpm. Supernatant was decanted and cells were resuspended in 1 mL of Phosphate Buffered Saline (PBS) (135 mM Sodium Chloride, 2.7 mM Potassium Chloride, and 11 mM Phosphate, diluted from a 20x ultrapure grade stock solution purchased from Amresco). Cells collected from the uninduced library served as negative controls, and gate guides for no-expression cells. Cells collected from the wt LCR sequence served as baseline fluorescence guides. Any cells from the library that possessed fluorescence equal or greater to the 1% highest fluorescence detected from the wt cells were collected. Cells were transferred from solution directly into 5 mL of LB (without centrifuging) to allow recovery for approximately 10 minutes. The media was then spun down and cells were plated on LB agar with kanamycin. Cell sorting was performed using UT’s Core Facility FACS Aria. Confirmation of fluorescence patterns by 96-well plate reader experiments To confirm that each isolated colony from the random library presented a true mutant that exhibited gain-of-fluorescence relative to cells expressing the wild-type H6P-GFP, we rescreened all colonies obtained from the sorting experiment using a Cytation 3 plate reader. Specifically, we set up 200 µL overnights in LB and 50 µg/mL kanamycin of all ~400 colonies collected from the sorting on 96-well plates. After reaching saturation (the next morning), we subcultured each culture into 200 µL of fresh LB broth containing kanamycin (50 µg/mL) to obtain an OD600 of 0.05. After growing cells to an OD600 of 0.2-0.5, we induced these cultures with IPTG (final concentration 1mM). Following a 5-hour period post-induction, we resuspended cells in 100 µL of PBS and measured fluorescence (490 nm excitation/ 510 nm emission). These experiments were done in triplicates. After this screen, we selected and sequenced 20 colonies that exhibited at least a two-fold increase in fluorescence. Computational prediction of mRNA-anti-Shine-Dalgarno Affinity Nucleic Acid Package’s (NUPACK) [26] online server was used to predict the affinity between LCR sequences with the anti-Shine-Dalgarno sequence (5’-UCCUCCAC-3’). The following user


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inputs were used: RNA nucleic acid type at 37°C, 2 strand species, and 2 maximum strand complex size. The concentration of the strands was input as an equimolar 750 µM for each species, and the default Serra and Turner, 1995 RNA energy parameters were used. The sequences were analyzed and, in the cases where strand1-strand2 complexes were formed, the absolute value of the free energy of the secondary structure formed was used as the predicted affinity. In the cases where only strand1-strand1, strand2-strand2, or no complexes were formed, the affinity value was arbitrarily assigned as 0. Construction of the rational linker coding region library To construct the rational library of LCR sequences, we used QuikChange II (Agilent Technologies) Site-Directed Mutagenesis (SDM) kit, following instructions recommended by the manufacturer. Clones that proved to be more challenging (due to increasing GC-content) were synthesized by Genscript. All clones were verified by DNA sequencing in our campus facilities. Flow Cytometry screening of the rational library Fluorescence measurements by flow cytometry were collected as previously reported [31]. Briefly, we cultured cells overnight at 37°C in LB broth containing 50 µg/mL kanamycin. We then diluted these cultures (1:100) into triplicate flasks containing 20 mL of LB/kanamycin (50 µg/mL) to a target OD600 of 0.05. We cultured these samples in a shaking incubator at 37°C to a desired OD600 of 0.6-0.8 (~2 hours), at which point we induced with IPTG (final concentration 1 mM) for five hours to trigger protein expression. We collected an initial fluorescence measurement (before induction) and 5 hours after induction. To measure the fluorescence, we collected 100 µL of cell culture, pelleted it at 15,000 rpm using Eppendorf tabletop centrifuge 5424 and resuspended in 1 mL of PBS. Flow cytometry data was collected using a BentonDickinson FACSCalibur with a 488 nm argon laser and 530 nm FL1 logarithmic amplifier. Medians of cell populations were attained using CellQuest Pro (BD) software. To control for variability in measurements, we used the wt construct with the unmutated LCR sequence as a basis to normalize each run. We ran triplicates of all samples. Western blotting analysis After culturing cells as described above, and after 5 hours of induction, we pelleted cells and snap froze them at -80°C. We performed Western blotting procedures with minimum modifications to previously published protocols [32]. Briefly, upon thawing on ice, we washed cells in 400 µL of PBS, resuspended in 300 µL of PBS and lysed by sonication. Cells were sonicated on ice in 3 bursts of 10 seconds with a probe sonicator voltage output of approximately 9 volts. 10 seconds of rest were included between each burst to prevent samples from overheating and consequently denaturing proteins. Following sonication, 100 µL were directly collected as total cell lysate, and the remaining ~200 µL of lysate were spun down for 4 minutes at 15,000 rpm. 100 µL of the clear supernatant was collected as the soluble fraction, on which Bradford Assay (utilizing Coomassie Protein Assay Reagent by Thermo Scientific) was run to quantify total soluble protein concentration. We conducted denaturing SDS-PAGE using a 12% bis-acrylamide gel and loaded ~30 µg of each protein sample in an appropriate amount of denaturing SDS loading buffer (125 mM tris (pH 6.8), 25% glycerol, 2% SDS, 0.01% bromophenol blue). All loading volumes were made constant by diluting protein samples with appropriate amounts of sterile water. The loading buffer contained 0.5% β-mercaptoethanol, which was added just before samples were boiled for protein denaturation. Following, SDS-


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PAGE, we transferred the gel to a 0.2 µm polyvinylidene difluoride (PVDF) membrane by electroblotting at 17V for 35 minutes using Trans-Blot Semi-Dry transfer cell (Bio-Rad). Detection of GFP was achieved by using an anti-GFP antibody (Roche/11814460001) at a 1:1,000 dilution, and an anti-mouse-HRP conjugate (Promega/W4021), at a 1:2,500 dilution. Loading controls were run using E. coli anti-RecA (Medical & Biological Laboratories (MBL)/MD-03-3) at a 1:10,000 dilution. All antibodies were diluted in 1% nonfat milk (in Tris Buffered Saline (TBS): 20 mM Tris, 500mM NaCl), and all membranes were blocked overnight at 4°C with 5% nonfat milk (in TBS) to minimize nonspecific binding. Because anti-GFP and anti-RecA were both generated in mice, it is possible to obtain band quantification for H6P-GFP and RecA without the need to strip the membranes. Anti-RecA was added first and allowed to interact with the membrane for one hour before being extensively washed with TTBS (TBS with 0.05% Tween 20), then TBS. Following that, membranes were immersed in solution containing anti-GFP, again washed, and finally blotted with anti-mouse-HRP. After washing, chemiluminescent detection using Bio-Rad’s Clarity Western ECL substrate, provides images of bands of interest (H6P) and loading control (RecA). Quantitation of Western bands was done utilizing ImageLab’s Western band detection protocol. To account for potential day-to-day variability in the data, we used relative values of all the quantified bands collected for each sample relative to the wt linker sequence in each case. Data for the wt linker sequence was collected as an internal control in every single experiment.

Supporting Information Coomassie stain and western analysis of linker clones as well as tabulated affinity values for rational library design, and β-galactosidase study are available free of charge via the Internet at http://pubs.acs.org.

Abbreviations E. coli: Escherichia coli GFP: Green fluorescence protein H6P: 3-hexulose 6-phosphate synthase LCR: Linker-coding region aa: amino acids aa/sec: amino acids per second HRP: Horseradish peroxidase IPTG: isopropyl-β-D-thiogalactopyranoside LB: Luria broth PBS: Phosphate-buffered saline SDM: site-directed mutagenesis SDS: Sodium dodecyl sulfate SDS-PAGE: sodium dodecyl sulfate polyacrylamide gel electrophoresis TBS: Tris-buffered saline TTBS: Tween 20 – Tris-buffered saline rpm: revolutions per minute β-gal: β-galactosidase


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aSD: anti-Shine-Dalgarno mRNA-aSD: messenger RNA – anti-Shine-Dalgarno PVDF: polyvinylidene difluoride

Author Information McKetta Department of Chemical Engineering, University of Texas at Austin, 200 E. Dean Keeton St., Stop C0400, Austin TX 78712 Corresponding Author: [email protected] Author contributions: Designed research: N.C.C., T.A.H, K.A.V., L.M.C.; performed experiments: N.C.C., T.A.H, K.A.V.; analyzed data: K.A.V., L.M.C.; wrote paper: N.C.C., T.A.H, K.A.V., L.M.C.

Acknowledments We would like to thank Jorge Vazquez-Anderson for his recommendations on experimental design and data analysis. Special thanks to the Waldo lab for their kind donation of the protein construct that this study is based on. We would also like to thank Jeff Thompson and Joe DeSautelle for their contributions to the early aspects of the project. This work is funded by the Welch Foundation [F-1756]; National Science Foundation CAREER Program [CBET-1254754]; Air Force Office of Scientific Research (AFOSR) Young Investigator Program [FA9550-13-10160]; and with Government support under and awarded by DoD, Air Force Office of Scientific Research, National Defense Science and Engineering Graduate (NDSEG) Fellowship, 32 CFR 168a.

References (1) Kramer, G., Boehringer, D., Ban, N., & Bukau, B. (2009). The ribosome as a platform for cotranslational processing, folding and targeting of newly synthesized proteins. Nat. Struct. Mol. Biol., 16(6), 589–597. http://doi.org/10.1038/nsmb.1614 (2) Kramer, G. (2001). Cotranslational folding — omnia mea mecum porto? The International Journal of Biochemistry & Cell Biology, 33(6), 541–553. http://doi.org/10.1016/S13572725(01)00044-9


12

Page 13 of 26

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(3) Berisio, R., Schluenzen, F., Harms, J., Bashan, A., Auerbach, T., Baram, D., & Yonath, A. (2003). Structural insight into the role of the ribosomal tunnel in cellular regulation. Nat. Struct. Biol., 10(5), 366–370. http://doi.org/10.1038/nsb915 (4) Nakatogawa, H., & Ito, K. (2004). Intraribosomal Regulation of Expression and Fate of Proteins. ChemBioChem, 5(1), 48–51. http://doi.org/10.1002/cbic.200300751 (5) Frank, J., Zhu, J., Radermacher, M., Verschoor, A., Lata, R. K., Penczek, P., Li, Y. (1995). A model of the translational apparatus based on a three-dimensional reconstruction of the Escherichia coli ribosome. Biochem. Cell Biol., 73(11-12), 757–765. http://doi.org/10.1139/o95084 (6) Frydman, J. (2001). FOLDING OF NEWLY TRANSLATED PROTEINS IN VIVO: The Role of Molecular Chaperones. Annu. Rev. Biochem., 70(1), 603–647. http://doi.org/10.1146/annurev.biochem.70.1.603 (7) Komar, A. A. (2009). A pause for thought along the co-translational folding pathway. Trends Biochem. Sci., 34(1), 16–24. http://doi.org/10.1016/j.tibs.2008.10.002 (8) Netzer, W. J., & Hartl, F. U. (1997). Recombination of protein domains facilitated by cotranslational folding in eukaryotes. Nature, 388(6640), 343–349. http://doi.org/10.1038/41024 (9) Young, R., & Bremer, H. (1976). Polypeptide-chain-elongation rate in Escherichia coli as a function of growth rate. The Biochem. J., 160(2), 185–194. (10) Ekman, D., Björklund, Å. K., Frey-Skött, J., & Elofsson, A. (2005). Multi-domain Proteins in the Three Kingdoms of Life: Orphan Domains and Other Unassigned Regions. J. Mol. Biol., 348(1), 231–243. http://doi.org/10.1016/j.jmb.2005.02.007


13


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Page 14 of 26

(11) Kiefhaber, T., Rudolph, R., Kohler, H.-H., & Buchner, J. (1991). Protein Aggregation in vitro and in vivo: A Quantitative Model of the Kinetic Competition between Folding and Aggregation. Nat. Biotechnol., 9(9), 825–829. http://doi.org/10.1038/nbt0991-825 (12) Komar, A. A., Lesnik, T., & Reiss, C. (1999). Synonymous codon substitutions affect ribosome traffic and protein folding during in vitro translation. FEBS Lett., 462(3), 387–391. http://doi.org/10.1016/S0014-5793(99)01566-5 (13) Dobson, C. M. (2003). Protein folding and misfolding. Nature, 426(6968), 884–890. http://doi.org/10.1038/nature02261 (14) Tsai, C.-J., Ma, B., Kumar, S., son, H. W. lf, & Nussinov, R. (2001). Protein Folding: Binding of Conformationally Fluctuating Building Blocks via Population Selection. Crit. Rev. Biochem. Mol. Biol., 36(5), 399–433. http://doi.org/10.1080/20014091074228 (15) O’Brien, E. P., Vendruscolo, M., & Dobson, C. M. (2012). Prediction of variable translation rate effects on cotranslational protein folding. Nat. Commun., 3, 868. http://doi.org/10.1038/ncomms1850 (16) Zhang, G., Hubalewska, M., & Ignatova, Z. (2009). Transient ribosomal attenuation coordinates

protein synthesis and co-translational folding. Nat. Struct. Mol. Biol., 16(3), 274–280. http://doi.org/10.1038/nsmb.1554 (17) Siller, E., DeZwaan, D. C., Anderson, J. F., Freeman, B. C., & Barral, J. M. (2010). Slowing Bacterial Translation Speed Enhances Eukaryotic Protein Folding Efficiency. J. Mol. Biol., 396(5), 1310–1318. http://doi.org/10.1016/j.jmb.2009.12.042 (18) Chen, W., Jin, J., Gu, W., Wei, B., Lei, Y., Xiong, S., & Zhang, G. (2014). Rational design of translational pausing without altering the amino acid sequence dramatically promotes soluble


14

Page 15 of 26

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


protein expression: A strategic demonstration. J. Biotechnol., 189, 104–113. http://doi.org/10.1016/j.jbiotec.2014.08.031 (19) Maertens, B., Spriestersbach, A., von Groll, U., Roth, U., Kubicek, J., Gerrits, M., Schäfer, F. (2010). Gene optimization mechanisms: A multi-gene study reveals a high success rate of fulllength human proteins expressed in Escherichia coli: Human Gene Optimization for Expression in E. coli. Protein Sci., 19(7), 1312–1326. http://doi.org/10.1002/pro.408 (20) Li, G.-W., Oh, E., & Weissman, J. S. (2012). The anti-Shine-Dalgarno sequence drives translational pausing and codon choice in bacteria. Nature, 484(7395), 538–541. http://doi.org/10.1038/nature10965 (21) Waldo, G. S., Standish, B. M., Berendzen, J., & Terwilliger, T. C. (1999). Rapid protein-folding assay using green fluorescent protein. Nat Biotech, 17(7), 691–695. http://doi.org/10.1038/10904 (22) Ito, K., Chiba, S., & Pogliano, K. (2010). Divergent stalling sequences sense and control cellular physiology. Biochem. Biophys. Res. Commun., 393(1), 1–5. http://doi.org/10.1016/j.bbrc.2010.01.073 (23) Vazquez-Anderson, J., & Contreras, L. M. (2013). Regulatory RNAs: Charming gene management styles for synthetic biology applications. RNA Biol., 10(12), 1778–1797. http://doi.org/10.4161/rna.27102 (24) Contreras-Martínez, L. M., & DeLisa, M. P. (2007). Intracellular Ribosome Display Via SecM Translation Arrest as a Selection for Antibodies with Enhanced Cytosolic Stability. J. Mol. Biol., 372(2), 513–524. http://doi.org/10.1016/j.jmb.2007.06.070 (25) Liu, C. C., Qi, L., Lucks, J. B., Segall-Shapiro, T. H., Wang, D., Mutalik, V. K., & Arkin, A. P. (2012). An adaptor from translational to transcriptional control enables predictable assembly of complex regulation. Nat. Methods, 9(11), 1088–1094. http://doi.org/10.1038/nmeth.2184


15


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 16 of 26

(26) Zadeh, J. N., Steenberg, C. D., Bois, J. S., Wolfe, B. R., Pierce, M. B., Khan, A. R., … Pierce, N. A. (2011). NUPACK: Analysis and design of nucleic acid systems. J. Comput. Chem., 32(1), 170– 173. http://doi.org/10.1002/jcc.21596 (27) Maloy, S. R., Stewart, V. J., & Taylor, R. K. (1996). Genetic analysis of pathogenic bacteria. NY: Cold Spring Harbor Laboratory Press. (28) Jacobson, R. H., Zhang, X.-J., DuBose, R. F., & Matthews, B. W. (1994). Three-dimensional structure of β-galactosidase from E. coli. Nature, 369(6483), 761–766. http://doi.org/10.1038/369761a0 (29) Robinson, C. R., & Sauer, R. T. (1998). Optimizing the stability of single-chain proteins by linker length and composition mutagenesis. Proc. Natl. Acad. Sci. U. S. A., 95(11), 5929-5934. (30) Contreras-Martinez, L. M., Boock, J. T., Kostecki, J. S., & DeLisa, M. P. (2012). The ribosomal exit tunnel as a target for optimizing protein expression in Escherichia coli. Biotechnol. J., 7(3), 354–360. http://doi.org/10.1002/biot.201100198 (31) Sowa, S. W., Vazquez-Anderson, J., Clark, C. A., De La Pena, R., Dunn, K., Fung, E. K., Contreras, L. M. (2015). Exploiting post-transcriptional regulation to probe RNA structures in vivo via fluorescence. Nucleic Acids Res., 43(2), e13–e13. http://doi.org/10.1093/nar/gku1191 (32) Gelderman, G., Sivakumar, A., Lipp, S., & Contreras, L. (2015). Adaptation of Tri-molecular fluorescence complementation allows assaying of regulatory Csr RNA-protein interactions in bacteria: Adaptation of Tri-Molecular Fluorescence. Biotechnol. Bioeng., 112(2), 365–375. http://doi.org/10.1002/bit.25351


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Slowing Translation between Protein Domains by ... - ACS Publications

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