Effect of Mutations on the Binding of Kanamycin-B to RNA Hairpins

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Effect of Mutations on the Binding of Kanamycin-B to RNA hairpins derived from the M. tuberculosis ribosomal A-site Amber R Truitt, Bok-Eum Choi, Jenny Li, and Ana Maria Soto Biochemistry, Just Accepted Manuscript • DOI: 10.1021/acs.biochem.5b00710 • Publication Date (Web): 11 Nov 2015 Downloaded from http://pubs.acs.org on December 6, 2015

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Effect of Mutations on the Binding of kanamycin-B to RNA hairpins derived from the M. tuberculosis ribosomal A-site†

Amber R. Truitt‡, Bok-Eum Choi‡, Jenny Li§, Ana Maria Soto‡§*

Department of Chemistry, Molecular Biology Biochemistry and Bioinformatics Program, Towson University, 8000 York Road, Towson, Maryland 21252

Running Title: Binding of Kanamycin-B to M. tuberculosis A-site

Key Words: RNA, kanamycin, kanamycin-B, paromomycin, tobramycin, A-site, decoding, aminoglycoside

*Corresponding Author: E-mail [email protected]; Phone 410-704-2605; Fax 410-704-4265

†

Funding: This work was funded in part by a Henry C. Welcome Fellowship (A.M.S.), a Raspet

Fellowship (B.C.), Fisher College of Science and Mathematics Undergraduate Research Grants (A.R.T and J.L.), Towson University Undergraduate Research Committee Grants (A.R.T, B.C. and J.L.) and a Towson University Faculty Development Research Committee Grant (A.M.S.).

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Abbreviations and Textual Footnotes

Page 4: Superscripts written as ‘number’/‘number’ refer to a position in M. tuberculosis/E. coli numbering. Page 4: Abbreviations: A-site: Aminoacyl site; 27-nt and 23nt: 27 and 23 nucleotides models, respectively; WT: wild type; A
G: A1400/1408
G; C
U: C1401/1409
U; GC
UA: C1401/1409
A and G1483/1491
U; 2AP: 2-Aminopurine; CD: Circular Dichroism; Tm: “melting” (unfolding) temperature.

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Abstract

Kanamycin is an aminoglycoside antibiotic used in the treatment of drug resistant tuberculosis. Mutations at the ribosomal RNA A-site have been associated with kanamycin-resistance in M. tuberculosis clinical isolates. Understanding the effect of these mutations on the conformation of the M. tuberculosis A-site is critical for understanding the mechanisms of antibiotic resistance in M. tuberculosis. In this work, we have studied RNA hairpins derived from the M. tuberculosis A-site: the wild type and three mutants at the following positions (M. tuberculosis/E. coli numbering):

A1400/1408
G,

C1401/1409
U,

and

the

double

mutant

G1483/1491

C1401/1409
UA. Specifically, we used circular dichroism, UV spectroscopy and fluorescence spectroscopy to characterize the conformation, stability and binding affinity for kanamycin-B and other aminoglycoside antibiotics to these RNA hairpins. Our results show that the mutations affect the conformation of the decoding site, with the mutations at position 1401/1409 resulting in significant destabilizations. Interestingly, the mutants bind paromomycin with weaker affinity than the wild type but they bind kanamycin-B with similar affinity than the wild-type. The results suggest that the presence of mutations does not prevent kanamycin-B from binding. Instead, kanamycin may promote different interactions with a third partner in the mutants compared to the wild-type. Furthermore, our results with longer and shorter hairpins suggest that the region of the A-site that varies among organisms may have modulating effects on the binding and interactions of the A-site.

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Introduction

Despite advances in its diagnosis and treatment, tuberculosis is a disease that still affects millions of people around the world (1). Of particular concern are the low cure rates of patients with multi-drug resistant (MDR) tuberculosis (1). Progress in new tuberculosis treatments is difficult in part due to significant gaps in our knowledge of the basic biochemistry of Mycobacterium tuberculosis (2). A detailed characterization of the molecules involved in the various aspects of M. tuberculosis infection will help us understand the molecular basis of drug resistance and develop new treatment options.

Aminoglycoside antibiotics were the first drugs to be effective against tuberculosis (3, 4, 5, 6) and continue to be used against this disease. Aminoglycosides are also used against a variety of diseases (5, 6) but their effect is sometimes hindered by resistance.

There are several

mechanisms of aminoglycoside resistance including export out of the cell by efflux pumps, reduced transport into the cell, enzymatic inactivation, and modification of their target (the bacterial ribosome) (5, 6). Generally speaking, enzymatic inactivation is the most important and clinically relevant mechanism of aminoglycoside resistance (4, 5). However, in the case of M. tuberculosis, the main mechanism of resistance appears to be modification of the ribosomal target (6). For instance, analysis of aminoglycoside resistant M. tuberculosis clinical isolates from Latvia (7) and China (8) has shown that the majority of mutations in high-level resistant strains are observed in the rrs gene, which encodes the 16S rRNA. Nevertheless, these studies also found that the mechanisms of aminoglycoside resistance in M. tuberculosis are diverse, highlighting the importance of investigating all mechanisms of resistance.

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Kanamycin is an aminoglycoside antibiotic and an important drug in the treatment of drug resistant tuberculosis (9, 10). However, tuberculosis strains can develop resistance to kanamycin (9), decreasing the drug treatment options for affected patients. One of the mechanisms of drug resistance to kanamycin involves mutations at the decoding A-site in the 16S ribosomal RNA, the kanamycin binding site (9, 11, 12). In particular, one study (9) identified three mutations in the genome of kanamycin-resistant M. tuberculosis clinical isolates.

These mutations are

localized in the rrs gene and correspond to the following positions in the 16S rRNA (using M. tuberculosis / Escherichia coli numbering): A1400/1408 to G (A
G), C1401/1409 to U (C
U) and the double mutant C1401/1409 to A, G1483/1491 to U (GC
UA). The decoding center of M. tuberculosis (Figure 1) is similar to the E. coli decoding center but differs in the base pairs in the lower stem (9). Since the base pairs at the lower stem differ in other organisms, including eukaryotes (13), it is possible that these mutations affect the conformation of M. tuberculosis in a different way than the more studied E. coli. For instance, one study (14) found that although the sequence of the lower stem may not be critical for specific aminoglycoside binding, binding is abolished when the AU base pair is replaced by a GC base pair (i.e. when the lower stem contains only GC or CG base pairs). Furthermore, some mutations have been found to be lethal in E. coli but viable in Mycobacterium smegmatis (15). Hence, understanding the effect of these mutations on the conformation of the M. tuberculosis decoding center is critical for understanding the mechanisms of antibiotic resistance in M. tuberculosis.

In this work, we have used circular dichroism, UV spectroscopy and fluorescence spectroscopy to characterize RNA hairpins derived from the M. tuberculosis A-site (Figure 1). Specifically,

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we have studied the wild type sequence and the three mutations associated with kanamycin resistance (9) in regard to their conformation, stability and binding affinity to kanamycin-B and other aminoglycoside antibiotics. Our results show that all mutations alter the stability of the decoding site, with the mutations at position 1401/1409 (M. tuberculosis/E. coli numbering) resulting in significant destabilizations.

Interestingly, the mutants bind paromomycin with

weaker affinity than the wild type but the mutants bind kanamycin-B with similar affinity than the wild-type. The results suggest that the presence of mutations does not prevent kanamycin-B from binding. Instead, kanamycin-B may stabilize an alternative conformation in the mutants; a conformation that may not create the bulging-out of the adenines in the internal loop necessary for antibacterial activity and hence may not interact with near cognate tRNAs in the same way as the aminoglycoside bound wild-type.

Experimental Procedures Materials: All RNA hairpins were purchased from Integrated DNA Technologies (Coralville, IA) and were purified by electrophoresis followed by electroelution. Purified molecules were extensively equilibrated in the appropriate buffer using Amicon centrifugal filters (Millipore, Billerica, MA). Aminoglycoside antibiotics were purchased from Sigma-Aldrich (St. Louis, MO) and used without further purification. All other reagents were purchased from SigmaAldrich or Fisher Scientific (Pittsburgh, PA) and used without further purification. RNA and Antibiotic Concentrations: RNA stock concentrations were obtained by measuring the absorbance of diluted RNA solutions at 260 nm and 85°C. Concentrations were obtained from Beer’s law, using extinction coefficients provided by the manufacturer (in mM-1cm-1): 232.3 (WT-23nt); 229.4 (A
G-23nt); 234.8 (C
U-23nt); 237.1 (GC
UA-23nt); 265.5 (WT-27nt);

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262.6 (A
G-27nt); 268.0 (C
U-27nt); 270.3 (GC
UA-27nt); and 254.5 (2AP-WT-27nt). Since aminoglycoside antibiotics may degrade in solution, all aminoglycoside solutions were freshly prepared on the same day of each experiment. Aminoglycoside concentrations were calculated based on gravimetric measurements, using the appropriate molecular weight. Since these compounds contain variable amounts of sulfate, their molecular weights were calculated based on the sulfate content provided on the manufacturer’s certificate of analysis of the corresponding lot number. These molecular weights were verified by measuring the amount of amino groups in pH titrations, as described before (16). UV unfolding experiments: Absorbance vs temperature profiles (UV melts) were obtained using a Cary100 spectrophotometer, equipped with a peltier.

The majority of experiments were

conducted using 1cm semi-micro quartz cuvettes and the RNA solutions were prepared as follows: 1000 µL of ~ 3 µM RNA solutions in 10 mM MOPS pH 7 were heated to 90 °C for 7 minutes and immediately cooled on ice for 7 minutes. The refolded RNA was placed in a cuvette and mixed with the appropriate stocks to obtain 1500 µL of solutions containing ~ 2 µM RNA, 0.2 to 1 mM MgCl2, 50 mM NaCl, and 10 mM MOPS pH 7. Some experiments were conducted using 0.1, 0.2 or 0.5 cm pathlength cuvettes and the RNA solutions were prepared as follows: 300 µL of 5 to 13 µM RNA solutions in 10 mM MOPS pH 7 were heated to 90 °C for 7 minutes and immediately cooled on ice for 7 minutes. The refolded RNA was placed in a cuvette and mixed with the appropriate stocks to obtain 410 to 820 µL of solutions containing 1.8 to 9.5 µM RNA, 0.2 to 1 mM MgCl2, 50 mM NaCl, and 10 mM MOPS pH 7. Solutions in 0.1, 0.2 or 0.5 cm pathlength cuvettes were topped with 30 to 50 µL of mineral oil (Nujol) to prevent evaporation at high temperature. RNA solutions were heated at a rate of 0.2 °C per minute while the absorbance at 260 and 280 nm were monitored and recorded.

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derivative of the resulting curves was analyzed manually, using procedures described before (17). Briefly, the Tm is the temperature at the top of the derivative peak and the van’t Hoff enthalpy was obtained using the following equation

, where T1 and T2 are the

temperatures at mid height of the derivative peak and 7 is a constant corresponding to monomolecular transitions. Since all hairpins unfold in monomolecular transitions, free energies (∆G) at 25 °C can be calculated as ∆G = ∆H (1− 298 Tm ) (17), where ∆H and Tm are the enthalpy and the unfolding temperature (in Kelvin) of the corresponding transition, respectively. More accurate enthalpies and Tms were obtained using the program Global Melt Fit, developed by David Draper (18, 19). This program performs a similar mathematical analysis as Meltwin and other fitting softwares (20). The Tms in the presence and absence of kanamycin-B were used to obtain estimates of the binding affinity at high temperature (at Tm), according to the , where Tmo is the melting temperature

following equation (21, 22):

(in Kelvin) in the absence of drug, Tm is the melting temperature in the presence of kanamycinB (in Kelvin), R is the gas constant, ∆H is the unfolding enthalpy of the RNA hairpin in the absence of kanamycin-B, L is the concentration of free kanamycin-B at Tm (estimated to be the total concentration of drug minus half of the concentration of RNA) and n is the number of drug molecules bound per RNA hairpin. Circular Dichroism Titrations: CD titrations were obtained using a Jasco J-815 Spectrometer, equipped with a peltier. Aminoglycoside-RNA binding isotherms were obtained by monitoring the circular dichroism signal at 222 nm upon addition of kanamycin-B or tobramycin. RNA solutions for circular dichroism titrations were prepared as follows: 1000 µL of ~ 9.4 µM RNA in 10 mM MOPS pH 7 were placed in a microcentrifuge tube, heated to 90 °C for 7 min, and

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cooled on ice for 7 min. The refolded RNA was placed in a cuvette and appropriate amounts of stocks were added to yield 2200 µL of final solutions containing ~ 4.2 µM RNA, 0.2 to 1 mM MgCl2, 50 mM NaCl, and 10 mM MOPS pH 7. Aminoglycoside solutions containing ~ 250 µM aminoglycoside, 0.2 to 1 mM MgCl2, 50 mM NaCl and 10 mM MOPS pH 7 were added to cuvettes containing RNA using aliquots of 2 to 100 µL. Samples were equilibrated for at least 4 minutes after each injection and the CD spectra was collected at least two times. The CD signal at 222 nm was corrected for dilution and was plotted as a function of aminoglycoside concentration. The resulting binding isotherms were fitted to a single-site binding model:

 [RNA] + [AA] + 1 K − ([RNA] + [AA] + 1 K) 2 − 4[AA][RNA]  S =  * (S Final − S Initial ) + S Initial 2[RNA]   (Equation 1) , where [RNA] is the initial concentration of RNA in the cuvette, [AA] is the total concentration of aminoglycoside after each addition, K is the binding affinity and S, SInitial, and SFinal represent the CD signal after a given addition, at the beginning of the experiment and at the end of the experiment, respectively. The curves presented are normalized based on their initial and final

 CDsignal − CDsignal Initial  signals using the following equation: 1−  . Final − CDsignal Initial   CDsignal Circular Dichroism Spectra: The CD spectrum of each hairpin in the presence and absence of kanamycin-B was collected using a Jasco J-815 CD Spectrometer equipped with a peltier. For each sample, at least two spectra were averaged and corrected by subtracting the CD spectra of the buffer, collected in the same cuvette. The molar ellipticity (in degrees x cm2 x dmol-1) was calculated by dividing the CD signal by the concentration of RNA (in mol/L) and multiplying the results by 100, as described before (23, 24). Samples for CD spectra were prepared in the same

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way as samples for CD titrations. CD spectra in the presence of kanamycin-B also contain 0.14 µmol of kanamycin-B. Fluorescence Titrations: Fluorescence titrations were obtained using a Horiba Jobin Yvon Fluoromax-4 spectrofluorometer. Aminoglycoside-RNA binding isotherms were obtained by monitoring the fluorescence emission upon addition of kanamycin-B or paromomycin to RNA. For a given experiment, two types of RNA solutions were prepared: mixed and 2AP-only solutions. In mixed solutions, 1000 µL of a solution containing 0.25 nanomoles of unlabeled RNA and 0.25 nanomoles of 2AP-labeled RNA in 10 mM MOPS pH 7 were placed in a microcentrifuge tube, heated to 90 °C for 7 minutes and cooled on ice for 7 minutes. The RNA refolded in this way was placed in a cuvette and mixed with the appropriate stocks to yield 2500 µL of final solutions containing 0.1 µM unlabeled RNA, 0.1 µM 2AP-labeled RNA, 10 mM MOPS pH 7, 50 mM NaCl and 1 mM MgCl2. 2AP-only solutions were prepared in the same way except that 0.5 nanomoles of 2AP-labeled RNA and no unlabeled RNA were used. RNA samples were titrated with 2 to 200 µL injections of 10 - 20 µM antibiotic solutions and were allowed to equilibrate at least 4 minutes after each injection. After equilibration, samples were excited at 310 nm and the emission at 375 nm and 390 nm were measured, corrected for dilution and used to create binding isotherms. The resulting binding isotherms were fitted to the binding equation listed above (Equation 1) to obtain the binding affinity of the 2AP-labeled RNA (K2APonly, from the 2AP-only titrations) and the apparent binding affinity of the 2AP-labeled RNA in the presence of the competing RNA (Kapp, from the mixed RNA titrations). Please note that only the concentration of labeled RNA (2AP-RNA) should be used in Equation 1. The binding affinity of each RNA (KUnlabel) was calculated from the apparent binding affinities using

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the following equation: K

app

K APonly = (Equation 2), where [RNAUnlabel] is the Unlabel Unlabel 1+ K [RNA ]

concentration of unlabeled RNA in the cuvette. Theoretically, [RNAUnlabel] represents the free unlabeled RNA concentration (which varies at each titration point) but simulation curves show that the error from using total unlabeled RNA concentrations is relatively low (15% or less) for relatively low binding affinities (1 µM-1 or lower). For higher affinities, KUnlabel values were estimated by calculating the corresponding equilibria in a spreadsheet, varying the value of KUnlabel until the calculated values matched each experimental data point. More accurate values were obtained fitting the appropriate equations using the software ProFit (QuantumSoft, Switzerland). The curves presented in the figures were normalized based on their initial and final signals using the following equation:

FluorSignal − FluorSignal Initial . The derivation of FluorSignal Final − FluorSignal Initial

Equation 2 as well as a detailed explanation of the equilibria and equations considered in these experiments is presented in Appendix 1.

Results Hairpin Design: The RNA hairpins used in this study were derived from the sequence of the 16S rRNA from Mycobacterium tuberculosis H37Rv (25) and are shown in Figure 1. Initial studies were conducted with a 23-nucleotide model hairpin, designed to include the positions equivalent to the minimum aminoglycoside binding site from its E. coli and eukaryotic counterparts (13, 26). The 23-nucleotide hairpin (Figure 1) model includes a universally conserved upper stem (13) consisting of residues 1486-1489 and 1396-1399 (M. tuberculosis numbering), an asymmetric internal loop consisting of residues 1484, 1485 and 1400 (M. tuberculosis numbering), and a lower stem, which shows more variability among organisms and consists of residues 1480-1483

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and 1401-1404 (M. tuberculosis numbering). A GAAA tetraloop was added (closing the upper stem) to stabilize the structure and the mutations related to kanamycin resistance (9) were incorporated in this 23-nucleotide model. Since some of the mutations proved to be very destabilizing, later experiments were conducted using a 27-nucleotide model in which G-C base pairs were added at the ends of the stems to further stabilize the structure. To prevent the formation of multimeric misfolded aggregates, all hairpins were refolded by snap cooling (see experimental procedures) before each experiment.

UV melts as a function of strand

concentration (Supplementary Information) show that the Tm of each transition does not change over a 10-fold concentration range, confirming the presence of the expected monomolecular hairpins. Effect of Mutations on the Thermal Stability of 23nt Hairpins: Unfolding experiments in the presence of 0.2 mM MgCl2 and 50 mM NaCl were conducted using the 23-nucleotides wild type and mutants. The unfolding curves are shown in Figure 2 and the thermodynamic profiles obtained from these experiments are shown in Table 1. Both the wild type and the A
G mutant unfold in two transitions while the C
U and GC
UA mutants unfold in a single transition. One possible interpretation of these profiles is that in the wild type and A
G mutant each stem unfolds independently resulting in the presence of two transitions. However, the C
U and GC
UA mutants may significantly destabilize the A-site model hairpin preventing the formation of one of the stems. If only one stem forms, the unfolding of the C
U and GC
UA mutants would display only one transition. Alternatively, the two transitions may correspond to the unfolding of the bases around the internal adenine loop followed by the simultaneous unfolding of the stems. In this case, the C
U and GC
UA mutants may destabilize the structure around the internal adenine loop so much that only the simultaneous unfolding of the

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stems is observed, which will appear as one transition in UV melts. Unfolding experiments at higher Mg2+ concentrations (1 mM) result in higher Tms (each Tm increases 5 to 7°C) but similar enthalpies and number of transitions (Table 1). This suggests that increasing the ionic strength increases the stability of each hairpin but does not promote the formation of additional base pairs in the C
U and GC
UA mutants (i.e. it does not promote the formation of the upper stem or of additional base pairs around the internal adenine loop). This suggests that the hairpins reach their stable conformation even at low ionic strengths. Hence, initial binding experiments were conducted at 0.2 mM MgCl2, 50 mM NaCl and 15 °C, conditions at which all hairpins should be stably folded, according to Figure 2. Circular Dichroism Titrations of 23nt Hairpins: The binding of kanamycin-B to the 23-nt hairpins was measured by monitoring the CD signal at 222 nm upon addition of kanamycin-B. The resulting binding isotherms (Figure 3) were fitted to a single-site binding model to yield the binding affinities listed in Table 2.

Our results show that all mutants bind kanamycin

(KCDAG23=0.20; KCDCU23=0.42; KCDGCUA23=0.27) with similar or slightly higher affinity than the WT hairpin (KCDWT23=0.23). Additional experiments using tobramycin, an antibiotic similar to kanamycin-B but with one –OH in ring I replaced by a –H, show that all mutants bind tobramycin (KCDAG23=0.19; KCDCU23=0.22; KCDGCUA23=0.20) with similar affinity than the WT hairpin (KCDWT23=0.13) (see Table 2). Thermal Stability of 27-nucleotide Model Hairpins: Since some of the mutations significantly destabilize our 23-nucleotide model, it is possible that the observed kanamycin-B affinity reflects the stabilizing effect of kanamycin-B rather than the intrinsic affinity of the mutants (i.e. some 23-nt mutants may take-up more kanamycin-B because it stabilizes their folded state). Hence GC base pairs were added at the end of the upper and lower stems of our model hairpin to obtain

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a more stable series of hairpins containing 27 nucleotides (Figure 1) and the concentration of Mg2+ was increased to 1 mM. Unfolding experiments using 27nt hairpins are shown in Figure 4 and the thermodynamic profiles obtained from these curves are summarized in Table 3. Our results show that all hairpins unfold in single transitions, display high Tms (TmWT27=73.5°C; TmAG27=74.3°C; TmCU27=67.7°C; TmGCAU27=70.4°C) and are stably folded at temperatures well above 40 °C. Unfolding experiments in the presence of saturating concentrations of kanamycinB indicate that all hairpins bind kanamycin-B, as demonstrated by the increase in Tm (TmKanaWT27=77.5°C; TmKanaAG27=78.5°C; TmKanaCU27=71.8°C; TmKanaGCAU27=74.3°C).

The

increase in Tm along with the unfolding enthalpy of the hairpins (without kanamycin) can be used to estimate the affinity of kanamycin-B for each RNA (at T = Tm). Although these affinities are calculated at different temperatures (at each hairpin’s Tm), the results suggest that the mutants bind kanamycin-B (KTmAG27=0.06 µM-1; KTmCU27=0.04 µM-1; KTmGCUA27=0.06 µM-1) with similar affinity than the wild type (KTmWT27=0.07 µM-1), as it was observed with the 23 nt hairpins. Circular Dichroism Titrations of 27nt Hairpins: In order to get more consistent estimates of the binding affinity, we conducted CD titrations. Binding isotherms (Figure 5) obtained by plotting the CD signal at 222 nm as a function of kanamycin-B concentration were fitted to a single-site binding isotherm. The resulting binding affinities (Table 4) once again suggest that the mutants bind kanamycin-B (KCDAG27=0.2 µM-1; KCDCU27=0.2 µM-1; KCDGCUA27=0.3 µM-1) with equal or higher affinity than the wild type (KCDWT27=0.1 µM-1).

Since circular dichroism titrations

measure a coupled constant consisting of a binding event and a conformational change (KCD = Kbind x Kconf), it is possible that the measured affinities reflect a different conformational change in the mutants compared to the WT rather than a higher association between the mutants and

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kanamycin-B. Comparison of the CD spectra in the presence and absence of kanamycin-B (Figure 6) suggest that all molecules undergo a conformational change of similar magnitude, given the similarity in the difference spectra for each hairpin. However, it is worth noting that the molecules display similar but different spectra (i.e. the spectra are not superimpossable). Hence, although all molecules undergo a similar conformational change, the free energy required to achieve each different bound conformation may be different.

In order to measure the

association between kanamycin-B and the hairpins more directly, we conducted fluorescence titrations. Fluorescently Labeled Hairpin:

Hairpins with 2-aminopurine (2AP) bases have been

successfully used to monitor the binding of paromomycin to the E. coli A-site in other laboratories (27, 28).

Hence, we incorporated 2AP substitutions at position 1484 (M.

tuberculosis numbering), in analogy to the E. coli studies (27, 28), which used 2AP at the equivalent E. coli position 1492. To ensure that neither the mutations nor the 2AP substitutions significantly destabilize our model hairpin, fluorescence experiments were only conducted using the 27nt hairpin set. UV melts of the labeled WT hairpin (2AP-WT-27nt) indicate that the presence of the 2AP label does not destabilize the hairpin conformation, as indicated by the similarity in the unfolding profiles of 2AP-WT-27nt and WT-27nt (Table 3). Fluorescence titrations: Although the 2AP substitution did not decrease the stability of our hairpin, it is possible that it could change the conformation around the adenine internal loop region.

Thus, we performed control experiments in which we compared the binding of

paromomycin to the wild type (WT-27nt) and to the 2AP substituted hairpin (2AP-WT-27nt). In these fluorescence titrations, cuvettes containing a mixture of labeled and unlabeled hairpins (WT-27nt + 2AP-WT-27nt) were compared with cuvettes containing only labeled hairpins (2AP-

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WT-27nt). The results show that the mixed cuvette titration is shifted to the right (Figure 7A), displaying a delay in paromomycin binding. Since the experiments only monitor the labeled molecules, the observed delay indicates that 2AP-WT-27nt binds paromomycin with lower affinity than WT-27nt. Since the 2AP label may affect each of the mutants in a different way, experiments with labeled mutants may not reflect the intrinsic binding affinity of the mutations. Fluorescence competition experiments: To allow for a more consistent comparison among the various hairpins, we conducted fluorescent competition experiments in which all unlabeled hairpins were compared with a single fluorescently labeled RNA (rather than constructing fluorescently labeled versions of each mutant). Fluorescence competition experiments have been successfully used in other labs to measure the binding affinities of unlabeled RNAs (29). In these experiments, 5 cuvettes were prepared containing 2AP-WT-27nt, 2AP-WT-27nt+WT-27nt, 2AP-WT-27nt+A
G-27nt, 2AP-WT-27nt+C
U-27nt, and 2AP-WT-27nt+GC
UA-27nt. Experiments were conducted concurrently to avoid variability in antibiotic concentrations. Since only 2AP-WT-27nt can be monitored in these fluorescent titrations, the position of the binding isotherms (shifted to the right or left), will qualitatively indicate whether the unlabeled molecule binds with equal affinity (unshifted superimpossable curve), lower affinity (shifted to the left) or higher affinity (shifted to the right) than 2AP-WT-27nt. The apparent binding affinity calculated from these competition experiments can be used to calculate the affinity of each unlabeled RNA, as described in the experimental and appendix sections. To test the validity of this approach, we conducted experiments with paromomycin, which has been reported to bind the E. coli A
G mutant with lower affinity (26, 28) than the E. coli WT. Our results (Figure 7A, Table 4) show that the mutants indeed bind paromomycin with lower affinity (KFParoAG27=1.2 µM-1; KFParoCU27=2.0 µM-1; KFParoGCUA27=2.5 µM-1) than the WT (KFParoWT27=63.4 µM-1). Experiments

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with kanamycin-B (Figure 7B, Table 4) show that the WT and mutants bind kanamycin-B with similar

affinity

(KFKanaWT27=2.2

µM-1;

KFKanaAG27=2.3

µM-1;

KFKanaGCUA27=1.7 µM-1), consistent with our CD experiments.

KFKanaCU27=1.5

µM-1;

The overall results suggest

kanamycin-B binds the mutants and wild type with equal affinity and that the mechanism of kanamycin resistance may be more complex than a simple decrease in association by resistant strains.

Discussion Mutations in the A-site have been linked to kanamycin resistance in M. tuberculosis (9, 30). In particular, the three mutants studied in this work were identified in clinical isolates from patients with kanamycin-resistant tuberculosis. In order to understand how these mutations are linked to kanamycin resistance, it is important to understand their effect on the conformation of the M. tuberculosis rRNA and on the binding affinity of kanamycin. Throughout this work, we have used kanamycin-B, which has the same number of amino groups as paromomycin and tobramycin (five), potentially allowing a more straightforward comparison among these antibiotics. General Effect of Aminoglycoside Antibiotics: The aminoacyl site (A-site) is the place in the ribosome where tRNA binds. Correct protein synthesis requires that the correct tRNA binds the correct mRNA codon (31). It has been proposed that A1492 and A1493 (E. coli numbering) bulge out and interact with the codon-anticodon helix, with the energetic cost for this conformational change compensated by the favorable interactions between A1492/A1493 and the correct codon-anticodon helix (31, 32). Several studies have shown that aminoglycoside antibiotics bind to the A-site of bacterial ribosomes (33) and increase the error rate of the

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ribosome by stabilizing the incorporation of near-cognate tRNAs (31, 34). Structural studies (26, 31, 34) have shown that binding of aminoglycosides to the A-site bulges out A1492 and A1493 (E. coli numbering). Hence, it has been suggested that aminoglycosides stabilize the bulged out conformation, allowing non-cognate tRNAs to bind stably in the A-site despite imperfect interactions with the codon-‘near-cognate anticodon’ helix (31). 23-nt RNA Hairpins Conformation: Our UV melts show that our WT A-site model forms a stable structure. WT-23nt unfolds in two transitions with enthalpies of 27 and 43 kcal/mol for the first and second transition, respectively. This unfolding profile could be interpreted as the sequential unfolding of the stems or as the unfolding of the nucleotides around the adenine internal loop followed by the unfolding of the rest of the structure. A comparison between the experimental unfolding profiles (Tables 1 and 3) and profiles calculated based on the proposed structures shown in Figure 1 could provide some insight on the unfolding steps. It has been suggested that the unfolding enthalpies are largely attributable to base stacking interactions (35). Hence, a comparison between the experimental and calculated enthalpies could indicate whether the set of stacking interactions proposed in Figure 1 (i.e. the proposed structures) are reasonable representations of our hairpins. The nearest neighbor parameters for canonical Watson-Crick base pairs (36) combined with the parameters for a UU mismatch (37), predict an overall enthalpy of 59.6 kcal/mol with enthalpic contributions of about 28.7 and 34.5 kcal/mol for the upper and lower stems, respectively (see Figure 1). These predicted values do not consider the contribution of the internal adenine loop, which is expected to affect the stability of our hairpins (38), but suggest that the lower stem has a higher enthalpy than the upper stem.

These

theoretical enthalpies would be consistent with the unfolding of the upper stem first followed by unfolding of the lower stem. Alternatively, the two transitions may correspond to the unfolding

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of the base pairs around the adenine internal loop (including the adenine internal loop, the GC base pairs above and below it and the U-U mismatch; i.e. residues 1483 to 1487 and 1398 to 1401, in M. tuberculosis numbering), followed by the unfolding of the rest of the structure (including 5 canonical Watson-Crick base pairs and the GAAA tetraloop) (Figure 8A). We favor the latter assignment because it would also result in enthalpies of about 28.7 and 34.5 kcal/mol for the first and second transitions, respectively, and because it provides an explanation for the destabilization caused by the C
U and GC
UA mutants: These mutations result in less stable GU and UA base pairs under the internal adenine loop, destabilizing the structure around the loop and decreasing the stability of the first transition (to the point that this transition is not clearly observed under our experimental conditions). Consistent with this idea, our CD titrations show that C
U-23nt and GC
UA-23nt bind kanamycin-B with somewhat higher affinity than WT-23nt and A
G-23nt (although the experimental errors are very high). Thus, C
U-23nt and GC
UA-23nt may appear to take-up more kanamycin-B because it stabilizes their folded state. Alternatively, the bigger size and lower stability of their internal adenine loop may facilitate kanamycin-B binding. In either case, this higher binding affinity is consistent with the lower stability of the nucleotides around the adenine internal loop of C
U-23nt and GC
UA23nt. Yet another possible explanation for the two observed transitions would be the presence of a competing structure with 4 Watson-Crick base pairs, a 10-nucleotide loop and a 5-nucleotide 3’ tail (Figure 8B). This structure would probably have somewhat lower stability that the structures depicted in Figure 1 but could form to certain extent with the sequence of WT-23nt, A
G-23nt and C
U-23nt. It is worth noting that although C
U-23nt has only one clear transition, it has a very high baseline (Figure 2), which could represent a low percentage of this competing structure.

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The competing structure will not be very stable in CG
AU-23nt because it would only have 3 Watson-Crick base pairs and it is interesting to note that CG
AU-23nt has a very clean single transition. 27-nt RNA Model Design: Our initial 23-nt RNA model was designed to include the nucleotides in the decoding region of M. tuberculosis with minimum modifications (the only addition was the stabilizing GAAA tetraloop). Although this model was useful for identifying the most destabilizing mutations, our experiments suggest that this 23-nt model may not be fully folded in the presence of destabilizing mutations or may be complicated by the presence of competing structures. Hence, two additional base-pairs were added to create a 27-nt model. The 27-nt model proved to be more stable and it is of the same size as a model hairpin derived from the E. coli A-site used in other laboratories (14). Although the E. coli hairpin has a slightly different design, both our model hairpin and the E. coli hairpin have one stem stabilized by a tetraloop and the other stem stabilized by GC base pairs. Chemical probing and NMR studies (14) of the E. coli hairpin show that it represents a well-folded oligonucleotide in which the expected WatsonCrick base pairs of the upper and lower stems fold correctly, and in which the internal adenine loop is closed by base pairs formed by U1406-U1495 (E. coli numbering) and G1494-C1407 (E. coli numbering). Furthermore, an A1408
G (E. coli numbering) mutation was well tolerated in the E. coli hairpin (13), with the expected Watson-Crick, the U1406-U1495 (E. coli numbering) and the G1494-C1407 (E. coli numbering) base pairs correctly formed. Since our 27-nt hairpin and the E. coli hairpin have a similar sequence and design, we suggest that our WT-27nt and A
G-27nt hairpins form the expected Watson-Crick, U1398-U1487 (M. tuberculosis numbering), and G1486-C1399 (M. tuberculosis numbering ) base pairs. It is worth noting that even if all the expected base pairs form, the presence of the adenine internal loop is expected to

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affect the base stacking interactions of the nucleotides that surround it. For instance, the van’t Hoff enthalpy of unfolding the E. coli WT hairpin (13) is 25 kcal lower than the 88.6 kcal/mol calculated using the nearest neighbor analysis (36, 37) for the E. coli sequence. We observe a similar enthalpy difference between our calculated and experimental enthalpies suggesting that the adenine internal loop affects the stacks in our system in a similar way. Effect of Mutations on M. tuberculosis 27nt-RNA Conformation: WT-27nt unfolds in a single cooperative transition, with an enthalpy somewhat lower than the predicted -85.13 kcal/mol (36, 37). The difference may be attributed to the presence of the adenine internal loop, which may not allow perfect formation of the helices.

Our results show that one of the mutants

(A1400/1408
G) has somewhat higher thermal stability (higher Tm) than the WT while the other two mutants (C1401/1409
U and C1401/1409G1483/1491
AU) have lower Tms than the WT. The higher thermal stability of the A
G mutant is consistent with the results from other laboratories (13). This mutation results in mild structural changes in the E. coli A-site structure (including a different orientation of base 1400/1408), which we speculate may result in a less dynamic, more thermally stable structure. The other two mutants destabilize the structure, particularly the C
U mutant, which may not be able to promote optimum interactions around the adenine internal loop even in the 27nt model (as indicated by its low unfolding enthalpy). Our results suggest that decreasing the stability of the GC base pair next to the adenine internal loop (G1483/1491C1401/1409) may severely affect some of the base-pairs and/or stacking interactions in the adenine internal loop, perhaps propagating the effect to the upper stem. The more severe destabilization of the C
U mutant compared to the GC
UA mutant suggest that this effect may be related to the stability of the base pair at this position, since AU base pairs are generally more stable than GU base pairs (39).

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Effect of Mutations on Kanamycin-B Binding: Several studies have identified important nucleotides in the binding of aminoglycosides to the E. coli A-site (14, 40, 41), which include the positions tested in our mutants.

Furthermore, since our three mutants are associated with

kanamycin resistance, we had expected the mutants to bind kanamycin-B with lower affinity than the WT. However, our results suggest that all three mutants bind kanamycin-B with similar or slightly higher affinity than the WT. The molecules bind paromomycin with the expected pattern where the affinity decreases from about 63 µM-1 for the wild type to about 1 to 3 µM-1 for the mutants. Structural studies with the A
G mutation in the E. coli A-site indicate that this mutant cannot undergo the same paromomycin-induced conformational change as the wild type, resulting in the loss of some paromomycin-RNA contacts (26). Kanamycin and paromomycin have similar rings I and II but differ in the linkage of ring III (34). Since all hairpins bind kanamycin with the same relatively low affinity of about 1 to 3 µM-1, we speculate that the different orientation of ring III may not permit some of the contacts that are possible with paromomycin. Hence, the mutants lose affinity for paromomycin because they lose some key interactions but kanamycin was not able to make those interaction with the wild type so all mutants and wild type display the same relatively low affinity. Kanamycin Resistance: Since the mutations may not change the affinity for kanamycin-B, we envision three possible reasons that may explain how these mutations are related to kanamycin resistance. First, it is possible that the conformational change induced by the mutants results in a conformation that does not stabilize the near-cognate tRNA sufficiently to cause errors in translation. This could be because the adenines in the internal loop (A1484 and A1485, M. tuberculosis numbering) may not bulge out when kanamycin-B binds the mutants. The small difference in conformation between the WT and the mutants expected in this scenario is

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consistent with our CD spectra (Figure 6) and our UV melts (Figures 2 and 4), which display that although all molecules undergo a conformational change of similar magnitude upon kanamycin binding, the conformation of each hairpin may be different. Although the exact conformation of each hairpin will require structural measurements (by NMR or crystallography), the fact that the CD spectra are not superimposable and that the UV melts don’t have the same thermodynamic parameters suggest that there may at least be small differences in the conformational change induced by kanamycin. Furthermore, experiments from another laboratory (42) have shown that a small difference in binding interactions may result in significant differences in the reduction of the mobility of the adenines in the internal loop. Their results suggest that the reduced mobility of the internal loop adenines is a more important determinant of antibacterial activity than the binding affinity (42). A second possibility is that kanamycin interacts differently with a second partner (such as protein S12 or a nearby RNA helix) when these mutations are present. Lastly, it cannot be discarded that these mutations may arise in kanamycin resistant clinical isolates for reasons not directly related to the resistance. This is unlikely since 29 out of 43 kanamycinresistant clinical isolates displayed mutations (compared to zero out of 71 non-resistant isolates) (9). Furthermore, studies have shown that the minimum inhibitory concentration (MIC) of aminoglycosides increases in the presence of these mutations in E. coli (11) and M. smegmatis (15, 43). However, it is worth noting that not all clinical isolates contain rRNA mutations (9) and that the least destabilizing mutation A1400/1408
G is the most common one among the clinical isolates (26 out of 29) (9). It is possible that resistance arises through synergistic effects of various contributions and that the presence of these mutations contributes but is not the sole determinant of the observed resistance. 23nt vs 27nt Models: The results obtained with the 23nt model and the 27nt models are

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generally consistent with each other, except for the relative stability of the C
U and GC
UA mutants. The difference in Tm between WT-27nt and the mutants is 5.8 °C for C
U-27nt and only 3.1 °C for CG
AU-27nt. On the other hand, the Tm difference between the second transition of WT-23nt and the mutants is only 0.8 °C for C
U-23nt but 12.1 °C for CG
AU23nt. The fact that adding one base pair at the end of each helix affects the cooperativity of the transition (resulting in all molecules unfolding in a single cooperative transition) emphasizes the importance of the stability of the helical stems on the conformation of the adenine internal loop. We speculate that in the 23nt model, C
U is more stable because U1401/1409 could make a base pair with A1484/1492 in the adenine internal loop (Figure 8C), which may stabilize the lower helix enough to stabilize the adenine internal loop or promote the formation of the upper helix. Consistent with this idea, the UV melts of C
U-23nt display a high baseline at low temperature, which could reflect an unstable adenine internal loop or upper stem. The addition of a GC base pair at the end of the helix in the 27nt model may stabilize the lower helix enough to keep the G1483-U1401 (M. tuberculosis numbering) base pair in position. As a result, the stability of the 27-nt hairpins is governed by the closing base pair of the lower stem (which would make GC
UA-27nt more stable than C
U-27nt). Our results suggest that the stability of the lower helix has effects on the conformation of the adenine internal loop and suggest that the sequence variability of the lower stem among organisms may help modulate the interactions between the A-site adenine internal loop and its ligands.

Conclusion Our results show that kanamycin-B binds the wild type and kanamycin-resistant mutants of the M. tuberculosis A-site with similar affinities. However, the mutants may display different

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conformations than the wild type suggesting that kanamycin may promote different interactions with a third partner in the mutants compared to the wild-type. For example, the mutants may interact different with the codon-anticodon helix due to a different degree of bulging-out of the adenines in the internal loop. Furthermore, our results with longer and shorter lower stems suggest that the stability of the lower stem may be important to the stability of the adenine internal loop. Since the lower stem varies among organisms, it is possible that the sequence of this region may have modulating effects in the binding and interactions of the A-site.

Appendix 1: Competition Experiments Calculations Competition experiments are often used in enzyme kinetics to measure the affinity of enzyme inhibitors drugs (44, 45, 46). Fluorescence competition experiments have been successfully used in the Draper laboratory (29) to measure the affinity of unlabeled RNA. Here we use a similar approach to compare the affinities of our WT hairpins with hairpins containing mutations.

The binding of a ligand to a labeled RNA (2APRNA): 2APRNA + ligand
2APRNA-Ligand can be monitored by measuring its fluorescence in the presence and absence of ligand. The equilibrium constant (K2APonly) can be written as: K2APonly =

ሾ2APRNA·Ligandሿ ሾ2APRNAሿሾLigandሿ

In competition experiments two different RNAs are present in one cuvette: one fluorescently labeled RNA (2APRNA) and an unlabeled RNA (RNAUnlabel). Both RNAs bind the ligand but with different affinities: 2APRNA + ligand
2APRNA-Ligand

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RNAUnlabel + ligand
RNAUnlabel-Ligand Although these represent independent equilibria, they are linked by the concentration of free ligand because they are in the same cuvette. Since only the labeled RNA can be monitored, the signal measured reports only on the first equilibrium but this equilibrium is altered because the unlabeled RNA consumes some of the free ligand. Hence, the presence of competing unlabeled RNA changes the measured binding affinity of 2APRNA to an apparent affinity: Kapp =

[2APRNA·Ligand] [2APRNA](ሾLigandሿ+[RNAUnlabel ·Ligand]

The latter equation can be rearranged to obtain the following expression:

ሾ2APRNAሿ[Ligand] ሾ2APRNAሿ[RNAUnlabel ·Ligand] 1 = + Kapp [2APRNA·Ligand] [2APRNA·Ligand]

When this equation is multiplied and divided by [Ligand][RNAUnlabel] and the appropriate equilibrium constants are replaced, the following equation is obtained: K

app

=

K2APonly 1+KUnlabel [RNAUnlabel ] (Equation 2)

Estimation of K values To estimate the binding affinities two experiments must be performed: one with the pure labeled RNA (from which K2APonly can be obtained) and one with an equimolar mixture of the labeled and unlabeled RNA (from which an estimate of Kapp could be obtained).

KUnlabel can be

estimated in three ways, with varying degrees of simplicity and accuracy. Method 1: Simplified Calculation This simplified method can be used when the values of KUnlabel are relatively low. In equation 2,

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the values of Kapp and K2APonly can be obtained by fitting the corresponding binding isotherm to a single binding site isotherm (equation 1).

Please note that only the total concentration of

2APRNA should be used in equation 1. Although Kapp does not strictly represent a single site binding isotherm, one obtains a reasonably good fit as long as the values of K2APonly and KUnlabel are relatively close or if KUnlabel < K2APonly. This is because relatively low KUnlabel values will not consume much of the free ligand and the 2APRNA equilibrium is uniformly disturbed. For instance, when KUnlabel = K2APonly, the 2APRNA equilibrium seems undisturbed and one obtains an excellent fit but the value obtained in the fit (Kapp) would be lower than the real K2APonly because only half of the ligand will appear to bind the labeled RNA. When the values of K2APonly, Kapp, and the 2APRNA concentration are used in equation 2, one obtains the correct value of KUnlabel.

Theoretically, [RNAUnlabel] in equation 2 represents the free unlabeled RNA

concentration (which varies at each titration point) and it is not readily accessible. However, simulation curves show that the error from using total unlabeled RNA concentrations is relatively low (15% or less) for relatively low binding affinities (~1 µM-1 or lower, when the value of K2APonly is set to 1 µM-1 and the concentration of 2APRNA is 0.1 µM). Method 2: Spreadsheet Estimation For higher affinities, KUnlabel values cannot be estimated using method 1 because the binding isotherms will display an altered “S” shape (instead of the typical rectangular hyperbola of a single site binding isotherm). This is because the unlabeled molecule will bind significant amounts of ligand and an initial delay will be observed in the fluorescence isotherms. However, the expected fluorescence signal can be calculated based on the free ligand concentration, KUnlabel, K2APonly, total concentrations of 2APRNA and RNAUnlabel, and the initial and final fluorescence signals. Five columns are set up in a spreadsheet including: (1) the free ligand concentration,

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which is chosen to be in a similar range as the experimental ligand concentrations, (2) the concentration of RNAUnlabel-ligand complex, (3) the concentration of 2APRNA-ligand complex, (4) the total ligand concentration, and (5) the expected signal. The last two columns can be plotted and compared with the experimental data. The values of KUnlabel and K2APonly are then varied until the simulated data superimposes the experimental data. The equations used to calculate each column are:

[RNAUnlabel • Ligand] =

ሾ2APRNA·Ligandሿ=

total K Unlabel [L]CRNA Unlabel

1+ K Unlabel [L]

(Equation A)

K2APonly ሾLሿCtotal 2APRNA

(Equation B)

1+K2APonly [L]

Total CLigand =ሾLሿ+ൣRNAUnlabel ·Ligand൧+[2APRNA·Ligand]

(Equation C)

(Equation D)

Total Total where [L] represents the concentration of free ligand, CLigand , CTotal 2APRNA , CRNAUnlabel , represent the

total concentrations of ligand, labeled RNA and unlabeled RNA, respectively.

Although

simulation curves show that the affinities calculated using this method come very close to the theoretical values, there is no unbiased way of recognizing a good fit from a poor fit (other than visual). More accurate values can be calculated using method 3. Method 3: Fitting Multiple Equilibria Equations B and D (from method 2) can be combined to yield a relationship between the free ligand concentration and the observed signal. To correlate such relationship to the experimental

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data, the free ligand concentration can be calculated in analogy to the method described by Wang and Jiang (47):

[L] = − where

S=

U 2 T  2 +  cos  U − 3S 3 3 3 U=

1 K

2APonly

1 K

2APonly

K

T=arccos ‫ۇ‬ ‫ۉ‬

Unlabel

+

1 K

Unlabel

+CTotal 2APRNA

(Equation E)

Total +2[2APRNA]Total -CLigand

1 K

2APonly

+

1 K

Unlabel

Total -CLigand

;

1 K

2APonly

+

1 K

Unlabel

; and

Total -2U3 +9US+( 27CLigand ൗK2APonly KUnfold ) ‫ۊ‬

2ට(U2 -3S)

‫ی‬

3

Equations B, D and E can be combined in one equation to fit the experimental data using a nonlinear fit. Fitting the resulting equation using the software ProFit (QuantumSoft, Switzerland) yields unbiased and accurate KUnfold values.

Supporting Information A supporting figure showing Tm as a function of strand concentration is available for free on the ACS website.

Acknowledgements We thank Dr. Stephen Scales for proofreading our manuscript, and Mr. George Kram, Mr. Jeff Klupt and Ms. Leetta Abner for their assistance with the equipment and various supplies needed for this work.

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References 1. World Health Organization, Global Tuberculosis Report 2014, Accessed on April 15, 2015. http://www.who.int/tb/publications/global_report/en/ 2. Russell, D. G., Barry, C. E. 3rd, Flynn, J. L. (2010) Tuberculosis: what we don't know can, and does, hurt us. Science 328, 852-856 3. Smith,T., Wolff, K.A., Nguyen, L. (2013) Molecular Biology of Drug Resistance in Mycobacterium tuberculosis. Curr Top Microbiol Immunol. 374, 53-80 4. Magnet, S., Blanchard, J.S. (2005) Molecular Insights into Aminoglycoside Action and Resistance. Chem Rev. 105, 477-497 5. Ramirez, M.S., Tolmasky. M.E. (2010) Aminoglycoside modifying enzymes. Drug Resist Updat. 13, 151-171 6. Vakulenko, S.B., Mobashery, S. (2003) Versatility of aminoglycosides and prospects for their future. Clin Microbiol Rev. 16, 430-450. 7. Bauskenieks, M., Pole, I., Skenders, G., Jansone, I., Broka, L., Nodieva, A., Ozere, I., Kalvisa, A., Ranka, R., Baumanis, V. (2015) Genotypic and phenotypic characteristics of aminoglycoside-resistant Mycobacterium tuberculosis isolates in Latvia. Diagn Microbiol Infect Dis. 81, 177-182. 8. Du, Q., Dai, G., Long, Q., Yu, X., Dong, L., Huang, H., Xie, J. (2013) Mycobacterium tuberculosis rrs A1401G mutation correlates with high-level resistance to kanamycin, amikacin, and capreomycin in clinical isolates from mainland China. Diagn Microbiol Infect Dis. 77, 138-142 9. Suzuki, Y., Katsukawa, C., Tamaru, A., Abe, C., Makino, M., Mizuguchi, Y., Taniguchi, H. (1998) Detection of kanamycin-resistant Mycobacterium tuberculosis by identifying

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mutations in the 16S rRNA gene. J Clin Microbiol. 36, 1220-1225. 10. Krüüner, A., Jureen, P., Levina, K., Ghebremichael, S., Hoffner, S. (2003) Discordant resistance to kanamycin and amikacin in drug-resistant Mycobacterium tuberculosis. Antimicrob Agents Chemother. 47, 2971-2973. 11. De Stasio E. A., Moazed D., Noller H. F., Dahlberg A. E. (1989) Mutations in 16S ribosomal RNA disrupt antibiotic-RNA interactions. EMBO J. 8, 1213–1216 12. Moazed D., Noller H. F. (1987) Interaction of antibiotics with functional sites in 16S ribosomal RNA. Nature 327, 389–394 13. Lynch, S.R., Puglisi, J.D. (2001) Structure of a eukaryotic decoding region A-site RNA. J Mol Biol. 306, 1023-1035. 14. Recht, M.I., Fourmy, D., Blanchard, S.C., Dahlquist, K.D., Puglisi, J.D. (1996) RNA sequence determinants for aminoglycoside binding to an A-site rRNA model oligonucleotide. J Mol Biol. 262, 421-436. 15. Pfister, P., Hobbie, S., Brüll, C., Corti, N., Vasella, A., Westhof, E., Böttger, E.C. (2005) Mutagenesis of 16S rRNA C1409-G1491 base-pair differentiates between 6'OH and 6'NH3+ aminoglycosides. J Mol Biol. 346, 467-75. 16. Smith, A.L., Kassman, J., Srour, K.J., Soto, A.M. (2011) Effect of salt concentration on the conformation of TAR RNA and its association with aminoglycoside antibiotics. Biochemistry 50, 9434-9445 17. Marky, L.A., Breslauer, K.J. (1987) Calculating thermodynamic data for transitions of any molecularity from equilibrium melting curves. Biopolymers 26, 1601-1620. 18. Draper, D.E and Gluick, T.C. (1995) Melting studies of RNA unfolding and RNA-ligand interactions, Methods Enzymol. 259, 281-305

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19. Draper, D.E., Bukhman, Y.V., and Gluick, T.C. (2001) Thermal methods for the analysis of RNA folding pathways, Curr. Protoc. Nucleic Acid Chem., Chapter 11, Unit 11.3 20. Schroeder, S.J., Turner, D.H. (2009) Optical melting measurements of nucleic acid thermodynamics. Methods Enzymol. 468, 371-387. 21. Schmitz, H.U., Hübner, W. (1993) A thermodynamic and spectroscopic study on the binding of berenil to poly d(AT) and to poly (dA) poly (dT). Biophys Chem. 48, 61-74. 22. Kaul, M., Pilch, D.S. (2002) Thermodynamics of Aminoglycoside-rRNA Recognition: The Binding of Neomycin-Class Aminoglycosides to the A Site of 16S rRNA. Biochemistry 41, 7695-7706 23. Tinoco, I., Sauer, K., Wang, J.C. and Puglisi, J.D. (2001) Physical Chemistry: Principles and Applications in Biological Sciences, 4th Edition, Prentice Hall, page 574 24. Kelly, S.M., Jess, T.J. and Price, N.C. (2005) How to study proteins by circular dichroism, Biochim Biophys Acta. 1751, 119-139 25. Kempsell, K.E., Ji, Y.E., Estrada, I.C., Colston, M.J., Cox, R.A. (1992) The nucleotide sequence of the promoter, 16S rRNA and spacer region of the ribosomal RNA operon of Mycobacterium tuberculosis and comparison with Mycobacterium leprae precursor rRNA. J Gen Microbiol. 138, 1717-1727. 26. Lynch, S.R., Puglisi, J.D. (2001) Structural origins of aminoglycoside specificity for prokaryotic ribosomes. J Mol Biol. 306, 1037-1058. 27. Barbieri, C.M., Kaul, M., Pilch, D.S. (2007) Use of 2-aminopurine as a fluorescent tool for characterizing antibiotic recognition of the bacterial rRNA A-site. Tetrahedron 63, 35673574. 28. Kaul, M., Barbieri, C.M., Pilch, D.S. (2004) Fluorescence-based approach for detecting and

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characterizing antibiotic-induced conformational changes in ribosomal RNA: comparing aminoglycoside binding to prokaryotic and eukaryotic ribosomal RNA sequences. J Am Chem Soc. 126, 3447-3453. 29. Bausch, S.L., Poliakova, E., Draper, D.E. (2005) Interactions of the N-terminal domain of ribosomal protein L11 with thiostrepton and rRNA. J Biol Chem. 280, 29956-29963. 30. Shcherbakov, D., Akbergenov, R., Matt, T., Sander, P., Andersson, D.I., Böttger, E.C. (2010) Directed mutagenesis of Mycobacterium smegmatis 16S rRNA to reconstruct the in vivo evolution of aminoglycoside resistance in Mycobacterium tuberculosis. Mol Microbiol. 77, 830-840 31. Carter, A. P., Clemons, W. M., Brodersen, D. E., Morgan-Warren, R. J., Wimberly, B. T. and Ramakrishnan, V. (2000). Functional insights from the structure of the 30S ribosomal subunit and its interactions with antibiotics. Nature 407, 340-348 32. Zeng, X., Chugh, J., Casiano-Negroni, A., Al-Hashimi, H., Brooks, C.L. III. (2014) Flipping of the Ribosomal A-site Adenines Provides a Basis for tRNA Selection. J. Mol Biol. 426, 3201-3213 33. Moazed, D., Noller, H.F. (1987) Interaction of antibiotics with functional sites in 16S ribosomal RNA. Nature 327, 389-394. 34. Vincens, Q., Westhof, E. (2001) Crystal Structure of Paromomycin Docked into the Eubacterial Ribosomal Decoding A site. Structure 9, 647-658 35. Searle, M.S., Williams, D.H. (1993) On the stability of nucleic acid structures in solution: enthalpy-entropy compensations, internal rotations and reversibility. Nucleic Acids Res. 21, 2051-2056 36. Xia, T., SantaLucia, J. Jr., Burkard, M.E., Kierzek, R., Schroeder, S.J., Jiao, X., Cox, C.,

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Turner, D.H. (1998) Thermodynamic parameters for an expanded nearest-neighbor model for formation of RNA duplexes with Watson-Crick base pairs. Biochemistry 37, 14719-14735. 37. Davis, A.R., Znosko, B.M. (2007) Thermodynamic Characterization of Single Mismatches Found in Naturally Occurring RNA. Biochemistry 46, 13425-13436 38. McCann, M.D., Lim, G.F.S., Manni, M.L., Estes, J., Klapec, K.A., Frattini, G.D., Knarr, R.J., Gratton, J.L., Serra, M.J. (2011) Non-nearest-neighbor dependence of the stability for RNA group II single-nucleotide bulge loops. RNA 17, 108–119. 39. Chen, J.L., Dishler, A.L., Kennedy, S.D., Yildirim, I., Liu, B., Turner, D.H., Serra, M.J. (2012) Testing the Nearest Neighbor Model for Canonical RNA Base Pairs: Revision of GU Parameters. Biochemistry 51, 3508–3522. 40. François, B., Russell, R.J., Murray, J.B., Aboul-ela, F., Masquida, B., Vicens, Q., Westhof, E. (2005) Crystal structures of complexes between aminoglycosides and decoding A site oligonucleotides: role of the number of rings and positive charges in the specific binding leading to miscoding. Nucleic Acids Res. 33, 5677-5690 41. Vicens, Q., Westhof, E. (2002) Crystal structure of a complex between the aminoglycoside tobramycin and an oligonucleotide containing the ribosomal decoding a site. Chem Biol. 9, 747-55. 42. Barbieri, C.M., Kaul, M., Bozza-Hingos, M., Zhao, F., Tor, Y., Hermann, T., Pilch, D.S. (2007) Defining the molecular forces that determine the impact of neomycin on bacterial protein synthesis: importance of the 2'-amino functionality. Antimicrob Agents Chemother. 51, 1760-1759. 43. Kalapala, S.K., Hobbie, S.N., Böttger, E.C., Shcherbakov, D. (2010) Mutation K42R in ribosomal protein S12 does not affect susceptibility of Mycobacterium smegmatis 16S rRNA

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A-site mutants to 2-deoxystreptamines. PLoS One 5, e11960 44. Berg, J. M., Tymoczko, J. L., Stryer, L. (2007), Biochemistry (6th ed.), New York: W. H. Freeman, page 1003. 45. Helfand, M.S., Bethel, C.R., Hujer, A.M., Hujer, K.M., Anderson, V.E., Bonomo, R.A. (2003) Understanding resistance to beta-lactams and beta-lactamase inhibitors in the SHV beta-lactamase: lessons from the mutagenesis of SER-130. J Biol Chem. 278, 52724-52729. 46. Hoffmann, D., Assfalg-Machleidt, I., Nitschko, H., von der Helm, K., Koszinowski, U., Machleidt, W. (2003) Rapid enzymatic test for phenotypic HIV protease drug resistance. Biol Chem. 384, 1109-1117. 47. Wang, Z.X. and Jiang, R.F. (1996) A novel two-site binding equation presented in terms of the total ligand concentration, FEBS Lett. 392, 245-249.

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Table 1: Unfolding Enthalpies of 23-nucleotide hairpins

Hairpin

WT-23nt AG-23nt CU-23nt CG
AU-23nt

First Transition Second Transition Tm Tm ∆H ∆G (25°C) ∆H ∆G kcal/mol kcal/mol kcal/mol kcal/mol 0.2 mM MgCl2, 50 mM NaCl 27 1.2 43 4.8 39.0°C 62.4°C 28 1.6 43 4.8 43.0°C 62.6°C --42 4.6 61.6°C --32 2.5 50.3°C

1 mM MgCl2 WT-23nt 23 1.5 42 5.3 45.0°C 67.7°C AG-23nt 24 1.9 44 5.7 69.0°C 50.0°C CU-23nt --41 5.1 67.5°C CG
AU-23nt --39 3.9 57.5°C All experiments used 2.13 µM of the corresponding RNA in 10 mM MOPS-NaOH pH 7. Enthalpy values are associated with a 10% error; free energy values are associated with ~13% error; Tm values vary ± 0.5 °C.

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Table 2: Binding Affinities of 23-nucleotide hairpins measured by Circular Dichroism

K (kanamycin B) K (tobramycin) (µM-1) (µM-1) WT-23nt 0.23 ± 0.03 0.13 ± 0.06 A
G-23nt 0.19 ± 0.04 0.20 ± 0.00 C
U-23nt 0.42 ± 0.12 0.22 ± 0.07 CG
AU-23nt 0.27 ± 0.08 0.20 ± 0.02 All experiments were conducted at 15 °C, using 4.25 µM RNA solutions in 10 mM MOPS-NaOH pH 7, 0.2 mM MgCl2, 50 mM NaCl. Hairpin

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Table 3: Unfolding Profiles of 27-nt hairpins in the presence and absence of kanamycin

Hairpin

∆H kcal/mol

WT-27nt A
G-27nt C
U-27nt CG
AU-27nt 2AP-WT-27nt

67 59 44 65 72

-1 ∆G (25°C) KTm (µM ) kcal/mol Kanamycin-B RNA alone 9.4 -73.5 °C 8.4 -74.3 °C 5.5 -67.7 °C 8.6 -70.4 °C 10.3 -74.7 °C

Tm

RNA + kanamycin-B WT-27nt 81 12.2 77.5 °C 0.07 ± 0.04 A
G-27nt 75 11.4 78.5 °C 0.06 ± 0.03 7.6 C
U-27nt 56 0.04 ± 0.02 71.8 °C CG
AU-27nt 73 10.4 74.3 °C 0.06 ± 0.04 All experiments used 2.13 µM of the corresponding RNA in 10 mM MOPS-NaOH pH 7, 1 mM MgCl2, 50 mM NaCl. Experiments with kanamycin-B also contain 32 µM kanamycinB. ∆H values are associated with 10% error; ∆G values are associated with ~11% error; Tm values vary ± 0.5 °C.

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Table 4: Binding Affinities of 27-nucleotide hairpins measured by Circular Dichroism and Fluorescence

Hairpin

KCD (µM-1) Kfluores (µM-1) Kfluores (µM-1) (kanamycin B) (kanamycin B) (paromomycin)

2AP-WT-27nt -1.3 ± 0.1 18.2 ± 1.6 WT-27nt 2.2 ± 1.0 63.4 ± 25 0.1 ± 0.05 A
G-27nt 0.2 ± 0.1 2.3 ± 0.9 1.2 ± 0.1 C
U-27nt 0.2 ± 0.07 1.5 ± 1.0 2.0 ± 1.5 CG
AU-27nt 0.3 ± 0.1 1.7 ± 0.8 2.5 ± 0.7 CD experiments were conducted at 20 °C, using 4.25 µM RNA solutions in 10 mM MOPS-NaOH pH 7, 1 mM MgCl2, 50 mM NaCl. Fluorescence experiments were conducted at 25 °C, using 0.2 µM total RNA (labeled + unlabeled) solutions in 10 mM MOPS-NaOH pH 7, 1 mM MgCl2, 50 mM NaCl

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Figure Legends

Figure 1: (A) Scheme of RNA model used in this work. Theoretical unfolding enthalpies derived from the nearest neighbor parameters listed in references (36) and (37) are depicted on the right side. Calculation of unfolding enthalpies also requires a -3.61 kcal/mol initiation penalty per hairpin (36).

(B) RNA Hairpins derived from the 16S RNA sequence of M.

tuberculosis. The nucleotides shown in italics are added to increase stability and are not part of the original sequence. The outlined “A” in WT-27nt is the position where a fluorescent 2aminopurine base was incorporated for fluorescence experiments. Numerical labels correspond to the M. tuberculosis/E. coli nomenclature. (C) Aminoglycosides: Kanamycin-B (left) has three rings and is a 4,6-disubstituted 2-deoxystreptamine antibiotic while paromomycin (right) has 4 rings and is a 4,5-disubstituted 2-deoxystreptamine antibiotic.

Tobramycin is the same as

kanamycin-B but has a –H instead of an –OH at position 3’ (ring I). Kanamycin-A is the same as kanamycin-B but it has an –OH instead of an –NH2 at position 2’ (ring I).

Figure 2: First derivative of unfolding experiments of 23-nt hairpins at 280 nm. Experiments were conducted in 10 mM MOPS-Na pH 7, 50 mM NaCl and 0.2 mM MgCl2. WT-23nt: black crosses, A
G-23nt: red circles, C
U-23nt: blue squares, GC
UA-23nt: green triangles.

Figure 3: Normalized CD titrations of 23-nt hairpins with kanamycin-B. Experiments were conducted at 15 °C in 10 mM MOPS-Na pH 7, 50 mM NaCl and 0.2 mM MgCl2. Curves are normalized based on their initial and final signals to make the initial signal 1 and the final signal zero. WT-23nt: black crosses, A
G-23nt: red circles, C
U-23nt: blue squares, GC
UA-23nt:

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green triangles.

Figure 4: First derivative of unfolding experiments of 27-nt hairpins at 280 nm. Experiments were conducted in 10 mM MOPS-Na pH 7, 50 mM NaCl and 1 mM MgCl2. WT-27nt: black crosses, A
G-27nt: red circles, C
U-27nt: blue squares, GC
UA-27nt: green triangles.

Figure 5: Normalized CD titrations of 27-nt hairpins with kanamycin-B. Experiments were conducted at 25 °C in 10 mM MOPS-Na pH 7, 50 mM NaCl and 1 mM MgCl2. Curves are normalized based on their initial and final signals to make the initial signal 1 and the final signal zero. WT-27nt: black crosses, A
G-27nt: red circles, C
U-27nt: blue squares, GC
UA-27nt: green triangles.

Figure 6: Molar ellipticity (deg·cm2/dmol) of 27-nt hairpins in the presence and absence of kanamycin-B. Experiments were conducted at 25 °C in 10 mM MOPS-Na pH 7, 50 mM NaCl and 1 mM MgCl2, 4.2 µM RNA and ~ 60 µM Kanamycin B (where needed). Kanamycin-B complexes are represented as solid lines, individual hairpins are represented as follows: WT27nt: crosses, A
G-27nt: circles, C
U-27nt: squares, GC
UA-27nt: triangles. The difference between the complex and free RNA spectra is represented as a dotted line.

Figure 7: Fluorescence competition experiments of 27-nt hairpins (using an excitation of 310 nm and an emission of 375 nm). Experiments were conducted in 10 mM MOPS-Na pH 7, 50 mM NaCl and 1 mM MgCl2. Titrations are labeled as follows: 2AP-WT-27nt alone: asterisks, mixture of 2AP-WT-27nt + WT-27nt: crosses, mixture of 2AP-WT-27nt + A
G-27nt: circles,

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mixture of 2AP-WT-27nt + C
U-27nt: squares, and mixture of 2AP-WT-27nt + GC
UA-27nt: triangles. All curves are normalized based on their initial and final 375 nm emission signals to make the initial signal zero and the final signal 1.

Figure 8: Folding of 23-nt hairpins. Panel A: Suggest assignment for the first and second transitions of WT-23nt. Panel B: This structure may compete with the folding depicted in Figure 1 for the 23-nt hairpins. Panel C: This alternative base pairing may form in C
U-23nt.

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(A) Upper Stem
Adenine Internal Loop
Lower Stem


(B)

(C)

Kanamycin-B

Paromomycin

Figure 1

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Figure 2

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Figure 3

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Figure 4

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WT-27nt

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5

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Figure 6

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Figure 7

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A

B

C

C
U-23nt

Figure 8

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For  Table  of  Contents  Use  Only            

1.0

0.8 A A A G C _G _C G_ C G U U G _C A A A G_C _ C_ G A U G _C C _G 5'

0.6 0.4 0.2

3'

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