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Reply to the reviewers
Manuscript number: RC-2024-02393
Corresponding author(s): Katja Petzold
1. General Statements [optional]
We thank the reviewers for recognising the impact of our manuscript. The reviewers noted the novelty of the miRNA bulge structure, the importance of the three observed binding modes and their potential for use in future structure-based drug design, and the possible importance of the duplex release phenomenon. We are also thankful for the relevant and constructive feedback provided.
Our responses to the comments are written point by point in blue, and any changes in the manuscript are shown in red.
2. Description of the planned revisions
In response to Reviewer 1 - major comment 2
Some of the data is over-interpreted. For example, in Figure 3A, it is concluded that supplementary regions are more important for weaker seeds. Only two 8-mer seeds are present among the twelve target sites and thus it might be difficult to generalize.
We found the relationship between seed type and the effect of supplementary pairing in our data intriguing. To further investigate this effect, we tested whether it exists in published microarray data from HCT116 cells transfected with six different miRNAs (Linsley et al., 2007; Argawal et al., 2015). Here we found that the for the two miRNAs (miR-103 and miR-106b) where we see an impact of supplementary pairing, the difference is primarily driven by 7mer-m8 seeds.
Since the effect appears to be specific to the miRNA, we would like to test whether it can be observed for miR-34a in a larger dataset. Therefore, we plan to transfect HEK293T cells with miR-34a and analyse the mRNA response via RNAseq. We will repeat the analysis shown above, using the predicted number of supplementary pairs to categorise the dataset into groups with or without the effect of supplementary pairing. We will then compare the three seed types within these groups.
In response to Reviewer 2 - minor comment 1, "why was the 34-nt 3'Cy3-labeled miR34a complementary probe shifted up in the presence of AGO?".
We plan to investigate the upper band, which we hypothesise is a result of duplex release, using EMSA to ascertain whether the band height agrees with the size of the duplex.
3. Description of the revisions that have already been incorporated in the transferred manuscript
Reviewer #1
Evidence, reproducibility and clarity
Sweetapple et al. Biophysics of microRNA-34a targeting and its influence on down-regulation
In this study, the authors have investigated binding of miR-34a to a panel of natural target sequences using EMSA, luciferase reporter systems and structural probing. The authors compared binding within a binary and a ternary complex that included Ago2 and find that Ago2 affects affinity and strengthens weak binders and weakens strong binders. The affinity is, however, generally determined by binary RNA-RNA interactions also in the ternary complex. Luciferase reporter assays containing 12 different target sites that belong to one of three seed-match types were tested. Generally, affinity is a strong contributor to repression efficiency. Duplex release, a phenomenon observed for specific miRNA-target complementarities, seems to be more pronounced when high affinity within the binary complex is observed. Furthermore, the authors use RABS for structural probing either in a construct in CIS or binding by the individual miRNA in TRANS or in a complex with Ago2. They find pronounced asymmetric target binding and Ago2 does not generally change the binding pattern. The authors observe one specific structural group that was unexpected, which was mRNA binding with bulged miRNAs, which was expected sterically problematic based on the known structures. MD simulations, however, revealed that such structures could indeed form.
This is an interesting manuscript that contributes to our mechanistic understanding of the miRNA-target pairing rules. The combination of affinity measurements, structural probing and luciferase reporters allow for a broad correlation of target binding and repression strength, which is a well-thought and highly conclusive approach. However, there are a number of shortcomings that are summarized below.
The manuscript is not easy to read and to follow for several reasons. First, many of the sub-Figures are not referenced in the text of the results section (1C, 1D, 2C, 4D), which is somewhat annoying. Figure 4A seems to be mis-labeled. Second, a lot of data is presented in suppl. Figures. It should be considered to move more data into the main text in order to make it easier for readers to evaluate and follow.
Thank you for bringing this to our attention. We have now revised the figure references accordingly.
We have relocated gel images of BCL2, WNT1, MTA2 and the control samples from Figure S3 and S4 to the main results (Figure 2A-B) to improve readability and provide controls and details that aid in clear understanding. Additionally, we have relocated panel C from Figure S6 to Figure 2C to enhance the clarity of our rationale for using polyuridine (pU) in our AGO2 binding assays.
The updated figure is shown below, with changes to the legend marked in red.
Figure 2. Binary and ternary____ complex binding affinities measured by EMSA. (A) Binary (mRNA:miR-34a) binding assays showing examples of BCL2, WNT1 and MTA2. (B) Ternary (mRNA:miR-34a-AGO2) binding assays showing examples of BCL2, WNT1, MTA2, and the three control targets PERFECT, SCRseed, and SCRall. The Cy5 labelled species is indicated with asterisk (*). F indicates the free labelled species (miR34a or mRNA), B indicates binary complex, and T indicates ternary complex. Adjacent titrations points differ two-fold in concentration, with maximum concentrations stated at the top right. Adjacent titration points for MTA2 differed three-fold to assess a wider concentration range. In theternary assay, miRNA duplex release from AGO2 was observed for amongst others BCL2, WNT1, PERFECT, and SCRseed (band indicated with B), while it was not observed for SCRall and MTA2. See Figures S3 and S4 for representative gel images for all targets. See Supplementary files 2 and 3 for all images and replicates. (C) Titrations with increasing miR-34a-AGO2 concentration against Cy5-labelled SCRall (left) or PNUTS (right) comparing the absence and presence of 20 μM polyuridine (pU) during equilibration. pU acted as a blocking agent, reducing nonspecific binding, as seen by the different KD,app values for SCRall and PNUTS after addition of 20 μM pU. Therefore, all final mRNA:miR-34a-AGO2 EMSAs were carried out in the presence of 20 μM pU. Labels are as stated above. (D) Individual binding profiles for each of the 12 mRNA targets assessed by electrophoretic mobility assay (EMSA). Each datapoint represents an individual experiment (n=3). Blue represents results for the binary complex, and green represents results for the ternary complex. Dotted horizontal lines represent the KD,app values, which are also stated in blue and green with standard deviations (units = nM). Note that the x-axis spans from 0.1 to 100,000 in CCND1, MTA2 and NOTCH2, whereas the remaining targets span 0.1 to 10,000.
Some of the data is over-interpreted. For example, in Figure 3A, it is concluded that supplementary regions are more important for weaker seeds. Only two 8-mer seeds are present among the twelve target sites and thus it might be difficult to generalize.
We have revised our wording to recognise that more 8-mer sites would be required to draw a stronger conclusion based on this hypothesis. This hypothesis would be interesting to confirm in a larger dataset but is unfortunately outside of the scope of this paper.
Our hypothesis also aligns with recent data from Kosek et al. (NAR 2023; Figure 2D) where SIRT1 with an 8mer and 7mer-A1 seed was compared. Only the 7mer-A1 was sensitive to mutations in the central region or switching all mismatched to WC pairs.
Page 21 now states:
"This result indicates that the impact of supplementary binding may be greater for targets with weaker seeds, as has been observed earlier in a mutation study of miR-34a binding to SIRT1 (Kosek et al., 2023), although a larger sample size would be needed to confirm this observation."
Furthermore, we found the relationship between seed type and the effect of supplementary pairing in our data intriguing. To further investigate this effect, we tested whether it exists in published microarray data from HCT116 cells transfected with six different miRNAs (Linsley et al., 2007; Argawal et al., 2015). Here we found that the for the two miRNAs (miR-103 and miR-106b) where we see an impact of supplementary pairing, the difference is primarily driven by 7mer-m8 seeds. We therefore plan to test whether the effect can be observed for miR-34a in a larger dataset. We have outlined our preliminary data and planned experiments in Section 2 - description of the planned revisions.
I did not understand why the CIS system shown in 4A is a good test case for miR-34a-target binding. It appears very unnatural and artificial. This needs to be rationalized better. Otherwise it remains questionable, whether these data are meaningful at all.
Thank you for pointing out the need for clearer rationalisation.
The TRANS construct, where the scaffold carries the mRNA targeting sequence, provides reactivity information for the mRNA side only, while the microRNA is bound within RISC, with the backbone protected by AGO2. Therefore, to gain information on the miR-34a side of each complex we used the CIS construct, which provides reactivity information from both the miRNA and mRNA. We used the miRNA and mRNA reactivities to calculate all possible secondary structures for the binary complex, and then compared these structures to the mRNA reactivity in TRANS to find which structure fitted the reactivity patterns observed in the ternary complex.
We have included an additional statement in the manuscript to clarify this point on pages 12-13:
"Two RNA scaffolds were used for each mRNA target; i) a CIS-scaffold: RNA scaffold containing both mRNA target and miRNA sequence separated by a 10 nucleotide non-interacting closing loop, and ii) a TRANS-scaffold: RNA scaffold containing only the mRNA target sequence, to which free miR-34a or the miR-34a-AGO2 complex was bound (Figure 4A). The CIS constructs therefore provided reactivity information on the miRNA side, which is lacking in the TRANS construct, and was used to complement the TRANS data."
It may be worthwhile noting that a non-interacting 10 nucleotide loop was inserted between then miRNA and mRNA of the CIS constructs, allowing the miRNA and mRNA strands to bind and release freely. The reactivity patterns of each mRNA:miRNA duplex were compared between CIS and TRANS, and showed similar base pairing (Figure 4D). Furthermore, we have previously compared the two scaffolds in our RABS methodology paper (Banijamali et al. 2022), where no differences were observed besides reduced end fraying in the CIS construct.
For the TRANS experiments, only one specific scaffold structure is used. This structure might impact binding as well and thus at least one additional and independent scaffold should be selected for a generalized statement.
For each construct, the potential of interaction with the scaffold was tested using the RNAstructure (Reuter & Mathews, 2010)package. Based on the results of this assessment, two different scaffolds were used for our TRANS experiments. The testing and use of scaffolds has now been clarified further on page 13:
"The overall conformation of each scaffold with the inserted RNA was assessed using the RNAstructure (Reuter & Mathews, 2010) package to ensure that the sequence of interest did not interact with the scaffold. If any interaction was observed between the RNA of interest and the scaffold, then the scaffold was modified until no predicted interaction occurred. The different scaffolds and their sequence details are shown in supplementary information (Table S1)."
We have previously examined the scaffold's effect on binding and structure during the development of the RABS method. We tested the same mRNA (SIRT1) in separate, independent scaffolds to verify the consistency of the results. An example of this can be found in the supplementary information (Figure S1a) of Banijamali et al. (2022).
Generally, it would be nice to have some more information about the experiments also in the result section. Recombinant Ago2 is expressed in insect cells and re-loaded with miR-34a, luciferase reporters are transfected into tissue culture cells, I guess.
We have now stated the cell types used for AGO2 expression and luciferase reporter assays in the results.
On page 17 we have included:
"Samples of each of the 12 mRNA targets, as well as miR-34a and AGO2, were synthesised in-house for biophysical and biological characterisation. Target mRNA constructs were produced via solid-phase synthesis while miR-34a was transcribed in vitro and cleaved from a tandem transcript (Feyrer et al., 2020), ensuring a 5' monophosphate group. AGO2 was produced in Sf9 insect cells."
"To measure the affinity of each mRNA target binding to miR-34a, both within the binary complex (mRNA:miR-34a) and theternary complex (mRNA:miR-34a-AGO2), we optimised an RNA:RNA binding EMSA protocol to suit small RNA interactions. The protocol is loosely based on Bak et al. (2014)36, with major differences being use of a sodium phosphate buffering system so as not to disturb weaker interactions (James et al., 1996; Stellwagen et al., 2000), supplemented with Mg2+ as a counterion to reduce electrostatic repulsion between the two negatively charged RNAs (Misra & Draper, 1998), and fluorescently labelled probes."
Page 19:
" We successfully tested various RNA backgrounds, including polyuridine (pU) and total RNA extract (Figure S6B) to block any unspecific binding. Ultimately, we supplemented our binding buffer with pU at a fixed concentration of 20 µM for the ternary assays to achieve the greatest consistency."
Page 20:
"Repression efficacy for the 12 mRNA targets by miR-34a was assessed through a dual luciferase reporter assay6. Target mRNAs were cloned into reporter constructs and transfected into HEK293T cells."
Page 22:
"To infer base pairing patterns and secondary structure for each of the 12 mRNA:miR-34a pairs, we used the RABS technique (Banijamali et al., 2023) with 1M7 as a chemical probe. All individual reactivity traces are shown in Figure S9. Reactivity of each of the 22 miR-34a nucleotides was assessed upon binding to each of the 12 mRNA targets within a CIS construct, containing both miR-34a and the mRNA target site separated by a non-interacting 10-nucleotide loop. The two RNAs can therefore bind and release freely within the CIS construct and reactivity information is collected from both RNA strands."
In the first sentence of the abstract, Argonaute 2 should be replaced by Argonaute only since other members bind to miRNAs as well.
Thank you for recognising this. It has now been corrected.
Significance
This is an interesting manuscript that contributes to our mechanistic understanding of the miRNA-target pairing rules. The combination of affinity measurements, structural probing and luciferase reporters allow for a broad correlation of target binding and repression strength, which is a well-thought and highly conclusive approach. However, there are a number of shortcomings.
We thank the reviewer for recognising the approach and impact of our work. In addition we thank the reviewer for identifying the need for further data to support our conclusions from the luciferase assays, which is something that we plan to address, as described in section 2.
Reviewer #2
Evidence, reproducibility and clarity
Summary:
Sweetapple et al. took the approaches of EMSA, SHAPE, and MD simulations to investigate target recognition by miR-34a in the presence and absence of AGO2. Surprisingly, their EMSA showed that guide unloading occurred even with seed-unpaired targets. Although previous studies reported guide unloading, they used perfectly complementary guide and target sets. The authors of this study concluded that the base-pairing pattern of miR-34a with target RNAs, even without AGO2, can be applicable to understanding target recognition by miR-34a-bound AGO2.
Major comments:
(Page 11 and Figure S4) The authors pre-loaded miR-34a into AGO2 and subsequently equilibrated the RISC with a 5' modified Cy5 target mRNA. Since properly loaded miR-34a is never released from AGO2, it is impossible for the miR-34a loaded into AGO2 to form the binary complex (mRNA:miR-34a) in the EMSA (guide unloading has been a long-standing controversy). However, they observed bands of the binary complex in Figure S4. The authors did not use ion-exchange chromatography. AGOs are known to bind RNAs nonspecifically on their positively charged surface. Is it possible that most miR-34a was actually bound to the surface of AGO2 instead of being loaded into the central cleft? This could explain why they observed the bands of the binary complex in EMSA.
Thank you for mentioning this crucial point which has been a focus of our controls. We have addressed this point in four ways:
Salt wash during reverse IMAC purification.
Separation of unbound RNA and proteins via SEC.
Blocking non-specific interactions using polyuridine.
Observing both the presence and absence of duplex release among different targets using the same AGO2 preparation and conditions.
Firstly, although we did not use a specific ion exchange column for purification, we believe the ionic strength used in our IMAC wash step was sufficient to remove non-specific interactions. We used A linear gradient with using buffer A (50 mM Tris-HCl, 300 mM NaCl, 10 mM Imidazole, 1 mM TCEP, 5% glycerol v/v) and buffer B (50 mM Tris-HCl, 500 mM NaCl, 300 mM Imidazole, 1 mM TCEP, 5% glycerol) at pH 8. The protocol followed recommendation by BioRad for their Profinity IMAC resins where it is stated that 300 mM NaCl should be included in buffers to deter nonspecific protein binding due to ionic interactions. The protein itself has a higher affinity for the resin than nucleic acids.
A commonly used protocol for RISC purification follows the method by Flores-Jasso et al. (RNA 2013). Here, the authors use ion exchange chromatography to remove competitor oligonucleotides. After loading, they washed the column with lysis buffer (30 mM HEPES-KOH at pH 7.4, 100 mM potassium acetate, 2 mM magnesium acetate and 2 mM DTT). AGO was eluted with lysis buffer containing 500 mM potassium acetate. Competing oligonucleotides were eluted in the wash.
As ionic strength is independent of ion identity or chemical nature of the ion involved (Jerermy M. Berg, John L. Tymoczko, Gregory J. Garret Jr., Biochemistry 2015), we reasoned that our Tris-HCl/NaCl/ imidazole buffer wash should have at comparable ionic strength to the Flores-Jasso protocol.
Our total ionic contributions were: 500 mM Na+, 550 mM Cl-, 50 mM Tris and 300 mM imidazole. We recognise that Tris and imidazole are both partially ionized according the pH of the buffer (pH 8) and their respective pKa values, but even if only considering the sodium and chloride it should be comparable to the Flores-Jasso protocol.
We have restated the buffer compositions below written the methods section more explicitly to describe this:
"Following dialysis, any precipitate was removed by centrifugation, and the resulting supernatant was loaded onto a IMAC buffer A-equilibrated HisTrap-Ni2+ column to remove TEV protease, other proteins, and non-specifically bound RNA. A linear gradient was employed using IMAC buffers A and B."
Secondly, after reverse HisTrap purification, AGO2 was run through size exclusion chromatography to remove any remaining impurities (shown Figure S2B).
Thirdly, knowing that AGO2 has many positively charged surface patches and can bind nucleic acid nonspecifically (Nakanishi, 2022; O'Geen et al., 2018), we tested various blocking backgrounds to eliminate nonspecific binding effects in our EMSA ternary binding assays. We were able to address this issue by adding either non-homogenous RNA extract or homogenous polyuridine (pU) in our EMSA buffer during equilibration background experiments. This allowed us to eliminate non-specific binding of our target mRNAs, as shown previously in Supplementary Figure S6. We appreciate that the reviewer finds this technical detail important and have moved the panel C of figure S6 into the main results in Figure 2C, to highlight the novel conditions used and important controls needed to be performed. If miR-34a were non-specifically bound to the surface of AGO2 after washing, this blocking step would render any impact of surface-bound miR-34a negligible due to the excess of competing polyuridine (pU).
Our EMSA results show that, using polyU, we can reduce non-specific interaction between AGO2 and RNAs that are present. And still, duplex release occurs despite the blocking step. It is therefore less likely that duplex release is caused by surface-bound miR-34a.
Finally, the observation of distinct duplex release for certain targets, but not for others (e.g. MTA2, which bound tightly to miR-34a-AGO2 but did not exhibit duplex release; see Figure 2), argues against the possibility that the phenomenon was solely due to non-specifically bound RNA releasing from AGO2.
In response to the reviewers statement "Since properly loaded miR-34a is never released from AGO2, it is impossible for the miR-34a loaded into AGO2 to form the binary complex (mRNA:miR-34a)" we would like to refer to the three papers, De et al. (2013) Jo MH et al. (2015), and Park JH et al. (2017), which have previously reported duplex release and collectively provide considerable evidence that miRNA can be unloaded from AGO in order to promote turnover and recycling of AGO. It is known that AGO recycling must occur, therefore there must be some mechanisms to enable release of miRNA from AGO2 to enable this. It is possible that AGO recycling proceeds via miRNA degradation (TDMD) in the cell, but in the absence of enzymes responsible for oligouridylation and degradation, the miRNA duplex may be released. As TDMD-competent mRNA targets have been observed to release the miRNA 3' tail from AGO2 (Sheu-Gruttadauria et al., 2019; Willkomm et al., 2022), there is a possible mechanistic similarity between the two processes, however, we do not have sufficient data to make any statement on this.
(Page 18 and Figure S5) Previous studies (De et al., Jo MH et al., Park JH et al.) reported guide unloading when they incubated a RISC with a fully complementary target. However, neither MTA2, CCND1, CD44, nor NOTCH2 can be perfectly paired with miR-34a (Figure 1A). Therefore, the unloading reported in this study is quite different from the previously reported works and thus cannot be explained by the previously reported logic. The authors need to explain the guide unloading mechanism that they observed. Otherwise, they might misinterpret the results of their EMSA and RABS of the ternary complex.
The three aforementioned studies have reported unloading/duplex release. However, they did not only report fully complementary targets in this process.
De et al. (2013) reported that "highly complementary target RNAs promote release of guide RNAs from human Argonaute2".
Subsequently, Park et al. (2017) reported: "Strikingly, we showed that miRNA destabilization is dramatically enhanced by an interaction with seedless, non-canonical targets."
A figure extracted from Figure 5 of Park et al. is shown below illustrating the occurrence of unloading in the presence of seed mismatches in positions 2 and 3 (mm 2-3). Jo et al. (2015) also reported that binding lifetime was not affected by the number of base pairs in the RNA duplex.
In addition to these three reports, a methodology paper focusing on miRNA duplex release was published recently titled "Detection of MicroRNAs Released from Argonautes" (Min et al., 2020).
Therefore, we do believe that the previously observed microRNA release is similar to our observation. Here we also correlate it to structure and stability of the complex.
(Page 20) The authors reported, "it is notable that the seed region binding does not appear to be necessary for duplex release." The crystal structures of AGO2 visualize that the seed of the guide RNA is recognized, whereas the rest is not, except for the 3' end captured by the PAZ domain. How do the authors explain the discrepancy?
In this manuscript, we intend to present our observations of duplex release. There are many potential relationships between duplex release and AGO2 activity, which we do not have data to speculate upon. Previous studies, such as Park et al. (2017) have also observed non-canonical and seedless targets leading to duplex release, supporting our findings. Additionally, other publications including McGearly et al. (2019) report 3'-only miRNA targets, Lal et al. (2009) have documented seedless binding by miRNA and their downstream biological effects, and Duan et al. (2022) show that a large number of let-7a targets are regulated through 3′ non-seed pairing.
It is also possible that duplex release is not coupled to classical repression outcomes, and does not need to proceed by the seed, but instead regulates AGO2 recycling before AGO2 enters the quality control mode of recognising the formed seed.
(Pages 22) The authors mentioned, "It follows that the structure imparted via direct RNA:RNA interaction remains intact within AGO2, highlighting the role of RNA as the structural determinant." A free guide and a target can start their annealing from any nucleotide position. In contrast, a guide loaded into AGO needs to start annealing with targets through the seed region. Additionally, the Zamore group reported that the loaded guide RNA behaves quite differently from its free state (Wee et al., Cell 2012). How do the authors explain the discrepancy?
The key point we would like to emphasise is that AGO does not seem to alter the underlying RNA:RNA interactions. The bound state in the ternary complex reflects the structure established in the binary complex. We do not aim to claim a specific sequence of events, as this interpretation is not possible from our equilibrium data. Our data indicates that the protein is flexible enough to accommodate the RNA structure that is favoured in the binary complex. This hypothesis is further supported by our MD simulation, which demonstrates the accommodation of a miRNA-bulge structure within AGO2.
Targets lacking seeds have been identified previously (McGeary et al. 2019, Park et al. 2017, Lal et al. 2009) and can bind to miRNA within AGO. Therefore, there must be a mechanism by which these targets can anneal within AGO, such as via sequence-independent interactions (as discussed in question 3).
With respect to Wee et al., (2012), which studied fly and mouse AGO2 and found considerable differences between the thermodynamic and kinetic properties of the two AGO2 species. Furthermore, they found different average affinities between the two species, with the fly AGO binding tighter the mouse. Following this logic, it is not unexpected that human AGO2 would have unique properties compared to those of fly and mouse.
Below is an extract from Wee et al., (2012):
"Our KM data and published Argonaute structures (Wang et al., 2009) suggest that 16-17 base pairs form between the guide and the target RNAs, yet the binding affinity of fly Ago2-RISC (KD = 3.7 {plus minus} 0.9 pM, mean {plus minus} S.D.) and mouse AGO2-RISC (KD = 20 {plus minus} 10 pM, mean {plus minus} S.D.) for a fully complementary target was comparable to that of a 10 bp RNA:RNA helix. Thus, Argonaute functions to weaken the binding of the 21 nt siRNA to its fully complementary target: without the protein, the siRNA, base paired from positions g2 to g17, is predicted to have a KD ∼3.0 × 10−11 pM (ΔG25{degree sign}C = −30.7 kcal mol−1). Argonaute raises the KD of the 16 bp RNA:RNA hybrid by a factor of > 1011."
In the Wee et al. (2012) paper, affinity data on mouse and fly AGO2 was collected via filter binding assays, using a phosphorothioate linkage flanked by 2′-O-methyl ribose at positions 10 and 11 of the target to prevent cleavage. They then compared the experimentally determined mean KD and ΔG values for each species to predicted values of an RNA:RNA helix of 16-17 base-pairs. No comparison was made between individual targets, and no experimental data was collected for the RNA:RNA binding. The calculated energy values were made based on a simple helix without taking into account any possible secondary structure features. Considering the different AGO species, alternative experimental setup, modified nucleotides in the tested RNA, and the computationally predicted RNA values compared to the averaged experimental values, we believe there is considerable reason to observe differences compared to our findings.
We have expanded our discussion on page 27 to the following:
"An earlier examination of mRNA:miRNA binding thermodynamics by Wee and colleagues (2012) found that mouse and fly AGO2 reduce the affinity of a guide RNA for its target61. Our data indicate that the range of miR-34a binary complex affinities is instead constricted by human AGO2 in the ternary complex - strengthening weak binders while weakening strong binders. The 2012 study reported different average affinities between the two AGO2 species, with the fly protein binding tighter the mouse. Following this logic, it is not unexpected that human AGO2 would have unique properties compared to those of fly and mouse."
The authors concluded that the range of binary complex affinities is constricted by human AGO2 in the ternary complex - strengthening weak binders while weakening strong binders. This may hold true for miR-34a, but it cannot be generalized. Other miRNAs need to be tested.
That is true, we have now adjusted the wording to encompass this more clearly, shown below. Testing of further miRNAs is the likely content of future work from us and others.
"Our data indicate that the range of miR-34a binary complex affinities is instead constricted by human AGO2 in the ternary complex - strengthening weak binders while weakening strong binders."
Minor comments:
(Figure S2) Why was the 34-nt 3'Cy3-labeled miR34a complementary probe shifted up in the presence of AGO?
We believe this observation is also indicative of duplex release. At the time that these activity assays were collected, we were not as aware of the presence of duplex release so did not test it further, assuming it may be due to transient interactions. We plan to investigate this via EMSA and have included this in the planned revisions (section 2).
2.(Page 17) Does the Cy3 affect the interaction of the 3' end of miR-34 with AGO2?
miR-34a-3'Cy5 was used for binary experiments only and the reverse experiment was conducted as a control (where Cy5 was located on the mRNA) (Figure S3b), showing no change in affinity/interaction when the probe was switched to the target. For ternary experiments the mRNA target was labelled on the 5' terminus, to make sure there was no interference with loading miR-34a into AGO2.
A Cy3 labelled RNA probe (fully complementary to miR-34a) was used to detect miR-34a in northern blots, but AGO2 interaction is not relevant here under denaturing conditions.
Otherwise, the 34-nt slicing probe had Cy3 on the 5 nt 3' overhang and should therefore not interact with AGO.
- Several groups reported that overproduced AGOs loaded endogenous small RNAs. The authors should mention that their purified AGO2 was not as pure as a RISC with miR-34a. Otherwise, readers might think that the authors used a specific RISC.
We have now improved our explanation of the loading efficiency to make it more clear to the reader that our AGO2 sample was not fully bound by miR-34a, and that all concentrations refer to the miR-34a-loaded portion of AGO2. The following text can be found in the results on page 18:
"The mRNA:miR-34a-AGO2 assay had a limited titration range, reaching a maximum
miR-34a-AGO2 concentration of 268 nM due to a 5% loading efficiency (see Figure S2D for loading efficiency quantification). The total AGO2 concentration was thus 20-fold higher than the miR-34a-loaded portion. Further increase in protein concentration was prevented by precipitation. Weaker mRNA targets (CD44, CCND1, and NOTCH2) did not reach a saturated binding plateau within this range, leading to larger errors in their estimated KD,app values. However, reasonable estimation of the KD,app was possible by monitoring the disappearance of the free mRNA probe. Note that we refer to the miR-34a-loaded portion of AGO2 when discussing concentration values for all titration ranges. To ensure AGO2 binding specificity despite low loading efficiency, a scrambled control was used (SCRall; lacking stable base pairing with miR-34a or other human miRNAs according to the miRBase database57). SCRall showed no interaction with miR-34a-AGO2 (Figure 2B)."
(Figure legend of Figure S5) Binding was assessed "by."
Thank you for pointing this out, it is now fixed.
(Page 17) It would be great if the authors could even briefly describe the mechanism by which the sodium phosphate buffer with magnesium does not disturb weaker interactions by citing reference papers.
We have now added a supplementary methods section to our manuscript and included the description below on page 10:
"We found that a more traditional Tris-borate-EDTA (TBE) buffer disrupted weaker RNA:RNA binding interactions (Supplementary Methods Figure M1). Borate anions form stable adducts with carbohydrate hydroxyl groups (James et al., 1996) and can form complexes with nucleic acids, likely through amino groups in nucleic bases or oxygen in phosphate groups (Stellwagen et al., 2000). This makes TBE unsuitable for assessment of RNA binding, particularly involving small RNA molecules, which typically have weaker affinities. We therefore adapted our buffer system to a sodium phosphate buffer supplemented with magnesium. Magnesium acts as a counterion to reduce electrostatic repulsion between the two negatively charged backbones by neutralisation (Misra et al., 1998)."
We have also clarified the buffer adaptions in our results section on page 17:
The protocol is loosely based on Bak et al. (2014)36, with major differences being use of a sodium phosphate buffering system so as not to disturb weaker interactions(James et al., 1996; Stellwagen et al., 2000), supplemented with Mg2+ as a counterion to reduce electrostatic repulsion between the two negatively charged RNAs(Misra & Draper, 1998), and fluorescently labelled probes. Original gel images and quantification are shown in supplementary Figures S3 and S4. All KD,app values are shown in Supplementary Table 1, and represent the mean of three independent replicates.
Figure M1. Comparison of Tris-borate EDTA (TBE) and sodium phosphate with magnesium (NaP-Mg2+) buffer systems for EMSA. Cy5-labelled miR-34a and unlabelled CD44 were equilibrated in the two different buffer systems, using the same titration range. No mobility shifts were observed in the TBE system, while clear binding shifts were observed in the NaP-Mg2+ system.
6.(Page 22) The authors cited Figure 4C in the sentence, "Comparison between CIS and TRANS ..." Is this supposed to be Figure 4D?
The reviewer was correct in their assumption, and this has now been corrected.
7.(Figure 6) Readers would appreciate it if the guide and target were colored in red and blue. The color codes have been used in most papers reporting AGO structures. The current color codes are opposite.
We have now adjusted the colour schemes throughout the manuscript, and Figure 6 has been modified to the following:
__"Figure 6. The miRNA-bulge structure is readily accommodated by AGO2 as shown by molecular dynamics simulation. __Panel (A) displays a snapshot of the all-atom MD simulation of miR-34a (red) and NOTCH1 (blue) in AGO2. The NOTCH1:miR-34a duplex is shown with AGO2 removed for clarity and is rotated 90{degree sign} to show the miRNA bulge and bend in the duplex. This NOTCH1:miR-34a-AGO2 structure is compared with (B), which shows the crystal structure of miR-122 (orange) paired with its target (purple) via the seed and four nucleotides in the supplementary region (PDB-ID 6N4O17), and (C), which shows the crystal structure of miR-122 (orange) and its target (green) with extended 3' pairing, necessary for the TDMD-competent state (PDB-ID 6NIT19). AGO2 is depicted in grey, with the PAZ domain in green, and the N-terminal domain marked with N. The miRNA duplexes in (B) and (C) feature symmetrical 4-nucleotide internal loops, whereas the NOTCH1 structure in (A) has an asymmetrical miRNA bulge with five unpaired nucleotides on the miRNA side and a 3-nucleotide asymmetry."
Significance
This paper will have a significant impact on the field if seed-unpaired targets can indeed unload guide RNAs. The authors may want to validate their results very carefully.
We thank the reviewer for recognising the significance of duplex release (or guide unloading) from AGO2. We agree that the observations should be tested rigorously and have outlined the actions we took to ensure validity in our AGO2 preparation.
__Reviewer #3 __
Evidence, reproducibility and clarity (Required):
In this manuscript, the authors use a combination of biochemical, biophysical, and computational approaches to investigate the structure-function relationship of miRNA binding sites. Interestingly, they find that AGO2 weakens tight RNA:RNA binding interactions, and strengthens weaker interactions.
Given this antagonistic role, I wonder: shouldn't there be an 'average' final binding affinity? Furthermore, if I understand correctly, not many trends were observed to correlate binding affinity with repression, etc.
Overall, there was no 'average' final binding affinity observed, as the binary assays had a much higher maximum (NOTCH2binary affinity was within the micromolar range) skewing the mean average of the binary affinities to 657 nM, versus 111 nM for the ternary affinities. We also compare the variances of the binary and ternary affinity datasets using the F-test and found that F > F(critical one tail) and thus the variation of the two populations is unequal (binary variation is significantly larger than ternary).
F-Test Two-Sample for Variances
binary affinity
ternary affinity
Mean
657.3
110.971667
Variance
2971596.1
24406.4012
Observations
12
12
df
11
11
F
121.754784
P(F
7.559E-10
F(critical one-tail)
2.81793047
We agree that the overall correlation between affinity and repression was not strong, although we found a stronger correlation within the miRNA-bulge group (Figure 5C and S7C). A larger sample size of miRNA bulge-forming duplexes would be needed to test the generalizability of this observation.
Given the context of the study - whereby structure is being investigated as a contributing factor to the interaction between the miRNA and mRNA, I find it interesting that the authors chose to use MC-fold to predict the structures of the mRNA, rather than using an experimental approach to assess / validate the structures. Thirty-seven RNAs were assessed; I think even for a subset (the 12 that were focused on in the study), the secondary structure should be validated experimentally (e.g., by chemical probing experiments, which the research group has demonstrated expertise in over the last several years). The validation should follow the in silico folding approach used to narrow down the region of interest. It is necessary to know whether an energy barrier (associated with the mRNA unfolding) has to occur prior to miRNA binding; this could help explain some of the unexplained results in the study. Indeed, the authors mention that there are many variables that influence miRNA regulation.
Indeed, experimentally validated structures offer valuable insights that cannot be obtained solely through sequence-based predictions. This is why we opted to employ our RABS method to experimentally evaluate the binary and ternary complex binding of our 12 selected targets (as depicted in Figures 4 and S9 and discussed in the text on pages 23-24). While we (in silico) assessed all 37 RNA targets that were experimentally confirmed at the time, selecting 12 to represent both biological and predicted structural diversity, it would have been impractical to experimentally pre-assess all the targets not included in the final selection. Our in-silico assessment was designed to narrow down the regions of interest and evaluate predicted secondary structures present. The pipeline is shown in Figure 1. Details of the code used in the in-silico analysis are provided in Supplementary File 1.
Regarding the energy of unfolding of mRNA, our constructs considered the isolated binding sites thus the effects of surrounding mRNA interactions were removed. We compared our affinities to dG as well as MFE and have now included this analysis in Figure S8A. Additionally, we have included the text on page 27-28 of the discussion:
"Gibbs free energy (G), which is often included in targeting prediction models as a measure of stability of the miRNA:mRNA pair12,62, correlated with the log of our binary KD,app values, using ΔG values predicted by RNAcofold (R2 = 0.61). There was a weaker correlation with the free energy values derived from the minimum free energy (MFE) structures predicted by RNAcofold (R2 = 0.41) (Figure S8A). This result highlights the contribution of unfolding (in ΔG) as being an important in predicting KD. The differences between ΔG and KD,app are likely primarily due to inaccurately predicted structures used for energy calculations."
Additionally, we assessed the free form of all mRNA targets via RABS (Figure S9) and observed that the seed of each free mRNA was available for miRNA binding (seeds of the free mRNA were not stably bound).
Finally, when designing our luciferase plasmids we used RNAstructure (Reuter & Mathews, 2010) to check for self-folding effects which could interfere with target site binding and ensured that all plasmids were void of such effects.
In the methods, T7 is italicized by accident in the T7 in vitro transcription section. Bacmid is sometimes written with a capital B and other times with a lower-cased b. The authors should be consistent. The concentration of TEV protease that was added (as opposed to the volume) should be described for reproducibility.
Thank you for pointing out these overlooked points. They have now been corrected.
In figure S2D, what is the second species in the gel on the right-hand side of the gel in the miR-34a:AGO lanes? The authors should mention this.
We believe that the faint upper band corresponds to other longer RNA species loaded into AGO2. As AGO2 is loaded with a diversity of RNA species, it is likely that some of them may have a weak affinity for the miR-34a-complementary probe, and therefore show up on the northern blot.
Figure S3B and S3A are referenced out of order in the text. In regard to S3A, what are the anticipated or hypothesized alternative conformations for NOTCH1, DLL1, and MTA2? There are really interesting things going on in the gels, also for HNF4a and NOTCH2. Can the authors offer some explanation for why the free RNA bands don't seem to disappear, but rather migrate slowly? Is this a new species?
The order of the figure references have now been updated, thank you for alerting us to this.
Figure S3A: For MTA2, the two alternative conformations are shown in Figure S9 and S10 (and shown below here, miR-34aseed marked in pink). It appears that a single conformation is favoured at high concentration (> 1 µM) while the two conformations are present at {less than or equal to} 1 µM. The RABS data for MTA2 also indicated multiple binding conformations, as the reactivity traces were inconsistent. We expect that the conformation shown on the left was most dominant within AGO2, based on the reactivity of the TRANS + AGO assays. However, we cannot exclude a possible G-quadruplex formation due to the high G content of MTA2 (shown below right).
Regarding NOTCH1 and DLL1, a faint fluorescent shadow was observed beneath the miR-34a bound band. The RABS reactivity traces indicated a single dominant conformation for these targets, so it is possible that the lower shadow observed was due to more subtle differences in conformation, such as the opening/closing of one or a few base pairs at the terminus or bulge, (i.e. end fraying). HNF4α and NOTCH2 appear to never fully saturate the miR-34a, so a small un-bound population remains visible on the gel. For NOTCH2 this free miR-34a band appears to migrate upwards, possibly due to overloading the gel lane with excess NOTCH2 (which are not observed in the Cy5 fluorescence image).
In the EMSA for Perfect, why does the band intensity for the bound complex increase then decrease? How many replicates were run for this? This needs to be reconciled.
As for all EMSAs, three replicates were carried out for each mRNA target and all gels are shown in Supplementary Files 2 and 3, for the binary and ternary assays respectively.
Uneven heat distribution across the gel can lead to bleaching of the Cy5 fluorophore. To address this, we we used a circulating cooler in our electrophoresis tank, as outlined in our methods (page 10). However, the aforementioned gel for one of thePERFECT sample replicates appears to have been evenly cooled. As the binding ratio (rather than total band volume) was used for quantification, the binding curve was unaffected, and this did not influence KD,app.
We have now replaced the exemplary gel for PERFECT in Figure S3 with a more representative and evenly labelled gel from our replicates (Cy5 fluorescence image shown below). The binding curve for PERFECT is also shown here:
The authors list that the RNA concentration was held constant at 10 nM; in EMSAs, the RNA concentration should be less than the binding affinity; what is the lowest concentration of protein used in the assays shown in S3A? Is this a serial dilution? It seems to me like the binding assays for MTA2, Perfect, and SRCseed might have too high of an RNA concentration. (Actually, now I see in the supplement the concentrations of proteins, and the RNA concentration is too high). Also, why is the intensity of bands for bound complex for SRCseed more intense than the free RNA?
Why are the binding affinity error bars so large (e.g., for NOTCH2 with mir-34a) - 6 uM +/- 3 uM?
No protein was used in the binary assays shown in Figure S3A. For the ternary assays in Figure S4, the maximum concentration of miR-34a-loaded AGO2 (miR-34a-AGO2) was 268 nM, with a serial dilution down to a minimum of 0.06 nM.
Optimal EMSA conditions require a constant RNA concentration that is lower than the binding affinity to accurately estimate high-affinity interactions.
For our tightest binders, such as SIRT1, we can confidently state that the KD,app is less than 10 nM, estimated at 0.4 {plus minus} 1.1 nM. Therefore, the accuracy of this estimation is reduced, and the standard deviation is larger than the estimated KD,app. As NOTCH2 bound miR-34a very weakly and did not reach a fully bound plateau, the resulting high error was expected. Consequently, we do not have the same level of certainty for extremely tight or weak binders. In this study, the relative affinities were of primary importance.
We have included on page 18:
As the Cy5-miR-34a concentration was fixed to 10 nM to give sufficient signal during detection, KD,app values below 10 nM have a lower confidence.
Regarding the control samples PERFECT and SCRseed, our focus was not on determining the exact KD,app of these artificial constructs. Instead, we were primarily interested in whether they exhibited binding and under which conditions. For SCRseed, we neither adjusted the titration range nor calculated KD,app. For PERFECT, the concentration was adjusted to a lower range of 30 nM - 0.001 nM to give a relative comparison with the other tight binder SIRT1. However, further reduction in RNA concentration was not pursued, as it already fell well below the 10 nM sensitivity threshold.
Regarding the intensity of the bound SCRseed band, we observed that the bound fluorophore often resulted in stronger intensity than for the free probe. This was observed for a number of the samples (PERFECT, BLC2, SCRseed). A previous publication reported that Cy5 is sequence dependent in DNA, that the effect is more sensitive to double-stranded DNA, and that the fluorophore is sensitive to the surrounding 5 base pairs (Kretschy, Sack and Somoza, 2016). It is likely that the same phenonenon exists in RNA.
For MTA2, the two alternative conformations (shown in Figure S9 and S10) make assessment of KD,app more difficult. As the higher affinity conformation did not reach a fully-bound plateau before the weaker affinity conformation appeared, the binding curve plateau (where all miR-34a was bound) reflected the weaker conformation KD,app. We increased the range of titration tested by using a three-fold serial dilution, but further reduction in RNA concentration would not have been fruitful as it already dropped below well below the 10 nM sensitivity range. Therefore the MTA2 binary complex had a higher error at (944 {plus minus} 274 nM) and lower confidence.
We then decided to run a competition assay to detect the weaker KD,app of MTA2. The assay was set up using the known binding affinity of CD44, which was labelled with Cy5 to track the reaction. MTA2 was titrated against a constant concentration of Cy5-CD44:miR-34a, and disruption of the CD44 and miR-34a binding was monitored. We fitted the data to a quadratic for competitive binding (Cheng and Prusoff., 1973) to calculate the KD,app for competitive binding, or KC,app.
We validated our competition assay by comparing it with our direct binding assays, specifically assessing CD44 in a self-competition assay. The CD44 KC,app (168 {plus minus} 24 nM; mean and SD of three replicates) was found to be consistent with the KD,app obtained from the direct assay (165 {plus minus} 21 nM).
As we wanted all affinity data to be directly comparable (using the same methodology), we compared the KD,app values obtained via direct assay in the manuscript. It appears that the competitive EMSA assay for MTA2 reflects the weaker affinity conformation observed in the direct assay.
It would be very helpful if the authors wrote in the Kds in Figure 2A in green and blue (in the extra space in the plots). This would help the reader to better understand what's going on, and for me, as a reviewer, to better consider the analysis/conclusions presented by the authors.
KD,app values are written in in green and blue in what is now Figure 2D (originally Figure 2A).
The authors state on page 18 that 'Interestingly, however, we did not observe a correlation between binary or ternary complex affinity and seed type.' They should elaborate on why this is interesting.
The prevailing view is that the miRNA seed type significantly influences affinity within AGO2. The largest biochemical studies of miRNA-target interactions to date, conducted by McGeary et al. (2019, 2022), used AGO-RBNS (RNA Bind-n-Seq) to reveal relative binding affinities. These studies demonstrated strong correlations between the canonical seed types and binding affinity. Therefore, we find it interesting that no such correlation was observed in our dataset (despite its small size).
We have now added to the manuscript (page 20):
"The largest biochemical studies of miRNA-target interactions to date (McGeary et al., 2019, 2022) used AGO-RBNS (RNA Bind-n-Seq) to extract relative binding affinities, demonstrating strong correlations between the canonical seed types and binding affinity. Therefore, it is intriguing that our dataset, despite its small size, showed no such correlation."
Figure 2C is not referenced in the text (the authors should go back through the text to make sure everything is referenced and in order). The Kds should be listed alongside the gels in Figure 2C.
Figure 2 has now been rearranged and updated, with KD,app values listed in what is now Figure 2D.
Figure 3B is rather confusing to understand.
We have now adapted Figure 3 to simplify readability. Panel B has now been moved to C, and we have introduced panel A (moved from Figure 2B). In Figure 3C (originally 3B) we have added arrows to indicate the direction of affinity change from binary to ternary complex, and moved the duplex release information to panel A. We thank the reviewer and think that the data is now much clearer.
Figure 3. AGO2 moderates affinity by strengthening weak binders and weakening strong binders. (A) Correlation of relative mRNA:miR-34a with mRNA:miR-34aAGO2 binding affinities. No seed type correlation is observed, seeds coloured, where 8mer is pink, 7mer-m8 is turquoise, and 7-mer-A1 is mauve. The slope of the linear fit is 0.48, and intercept on the (log y)-axis is 7.11. The occurrence of miRNA duplex release from AGO2 is marked with diamonds. (B) miR-34a-mediated repression of dual luciferase reporters fused to the 12 mRNA targeting sites. Luciferase activity from HEK293T cells co-transfected with each reporter construct, miR-34a was measured 24 hours following transfection and normalised to the miR-34a-negative transfection control. Each datapoint represents the R/F ratio for an independent experiment (n=3) with standard deviations indicated. SCRseed is a scrambled seed control, SCRall is a fully scrambled control, and PERFECT is the perfect complement of miR-34a. Dotted horizontal lines represent the repression values for the 22-nucleotide seed-only controls6 for the respective seed types, in the absence of any other WC base pairing. (C) Comparison of relative target repression with relative affinity assessed by EMSA. Blue represents mRNA:miR-34a affinity (binary complex), while green represents mRNA:miR-34a-AGO2 affinity (ternary complex). Arrows indicate the direction of change in affinity upon binding within AGO2 compared to the binary complex. It is seen that AGO2 moderates affinity bi-directionally by strengthening weak binders and weakening strong binders.
Page 20: Perfect should be italicized.
Thank you for bringing this to our attention, this how now been adjusted.
Have the authors considered using NMR to assess the base pair pattern formed between the miRNA:mRNA complexes (with / without AGO)? As a validation for results obtained by RABS? This could be helpful for the Asymmetric target binding section, the Ago increases flexibility section, and the three distinct structural groups section in the results. It is widely accepted that while chemical probing is insightful, results should be validated using alternative approaches. Distinguishing structural changes and protected reactivity in the presence of protein is challenging.
NMR provides high-resolution information on RNA base-pairing patterns, allowing us to compare our RABS results for SIRT1with those obtained via NMR (Banijamali et al., 2022) for the binary complex. For SIRT1, the RNA:RNA structures identified were consistent between both methods. However, using NMR to measure RNA:RNA binding within AGO2 is challenging due to the protein's large size. Currently, there are no published complete NMR structures of RNA within AGO2. The largest solution-state NMR structures published that include AGO consist solely of the PAZ domain. Our group has been working on method development using DNP-enhanced solid-state NMR to obtain structural information within the complete AGO2 protein, but the current resolution does not allow us to fully reconstruct a complete NMR structure. We hope that in the coming years, this will be a method to evaluate RNA within AGO. This limitation highlights the advantage of RABS in providing RNA base-pairing information within the ternary complex in solution.
Reviewer #3 (Significance (Required)):
The work is helpful for understanding how microRNAs recognize and bind their mRNA targets, and the impact Ago has on this interaction. I think for therapeutic studies, this will be helpful for structure-based design. Especially given the three types of structures identified to be a part of the interaction.
We thank the reviewer for their detailed remarks, especially concerning the importance of technical details the binding assays. We further thank the reviewer for recognising the potential impact of our work for rational design.
4. Description of analyses that authors prefer not to carry out
In response to Reviewer 2 - major comment 1, we prefer to not run an additional ion exchange purification on the AGO2 protein due to the reasoning discussed above, which is repeated here:
We have addressed this point in three ways:
Thank you for mentioning this crucial point which has been a focus of our controls. We have addressed this point in four ways:
Salt wash during reverse IMAC purification.
Separation of unbound RNA and proteins via SEC.
Blocking non-specific interactions using polyuridine.
Observing both the presence and absence of duplex release among different targets using the same AGO2 preparation and conditions.
Firstly, although we did not use a specific ion exchange column for purification, we believe the ionic strength used in our IMAC wash step was sufficient to remove non-specific interactions. We used A linear gradient with using buffer A (50 mM Tris-HCl, 300 mM NaCl, 10 mM Imidazole, 1 mM TCEP, 5% glycerol v/v) and buffer B (50 mM Tris-HCl, 500 mM NaCl, 300 mM Imidazole, 1 mM TCEP, 5% glycerol) at pH 8. The protocol followed recommendation by BioRad for their Profinity IMAC resins where it is stated that 300 mM NaCl should be included in buffers to deter nonspecific protein binding due to ionic interactions. The protein itself has a higher affinity for the resin than nucleic acids.
A commonly used protocol for RISC purification follows the method by Flores-Jasso et al. (RNA 2013). Here, the authors use ion exchange chromatography to remove competitor oligonucleotides. After loading, they washed the column with lysis buffer (30 mM HEPES-KOH at pH 7.4, 100 mM potassium acetate, 2 mM magnesium acetate and 2 mM DTT). AGO was eluted with lysis buffer containing 500 mM potassium acetate. Competing oligonucleotides were eluted in the wash.
As ionic strength is independent of ion identity or chemical nature of the ion involved (Jerermy M. Berg, John L. Tymoczko, Gregory J. Garret Jr., Biochemistry 2015), we reasoned that our Tris-HCl/NaCl/ imidazole buffer wash should have at comparable ionic strength to the Flores-Jasso protocol.
Our total ionic contributions were: 500 mM Na+, 550 mM Cl-, 50 mM Tris and 300 mM imidazole. We recognise that Tris and imidazole are both partially ionized according the pH of the buffer (pH 8) and their respective pKa values, but even if only considering the sodium and chloride it should be comparable to the Flores-Jasso protocol.
Secondly, after reverse HisTrap purification, AGO2 was run through size exclusion chromatography to remove any remaining impurities (shown Figure S2B).
Thirdly, knowing that AGO2 has many positively charged surface patches and can bind nucleic acid nonspecifically (Nakanishi, 2022; O'Geen et al., 2018), we tested various blocking backgrounds to eliminate nonspecific binding effects in our EMSA ternary binding assays. We were able to address this issue by adding either non-homogenous RNA extract or homogenous polyuridine (pU) in our EMSA buffer during equilibration background experiments. This allowed us to eliminate non-specific binding of our target mRNAs, as shown previously in Supplementary Figure S6. We appreciate that the reviewer finds this technical detail important and have moved the panel C of figure S6 into the main results in Figure 2C, to highlight the novel conditions used and important controls needed to be performed. If miR-34a were non-specifically bound to the surface of AGO2 after washing, this blocking step would render any impact of surface-bound miR-34a negligible due to the excess of competing polyuridine (pU).
Our EMSA results show that, using polyU, we can reduce non-specific interaction between AGO2 and RNAs that are present. And still, duplex release occurs despite the blocking step. It is therefore less likely that duplex release is caused by surface-bound miR-34a.
Finally, the observation of distinct duplex release for certain targets, but not for others (e.g. MTA2, which bound tightly to miR-34a-AGO2 but did not exhibit duplex release; see Figure 2), argues against the possibility that the phenomenon was solely due to non-specifically bound RNA releasing from AGO2.
In response to the reviewers statement "Since properly loaded miR-34a is never released from AGO2, it is impossible for the miR-34a loaded into AGO2 to form the binary complex (mRNA:miR-34a)" we would like to refer to the three papers, De et al. (2013) Jo MH et al. (2015), and Park JH et al. (2017), which have previously reported duplex release and collectively provide considerable evidence that miRNA can be unloaded from AGO in order to promote turnover and recycling of AGO. It is known that AGO recycling must occur, therefore there must be some mechanisms to enable release of miRNA from AGO2 to enable this. It is possible that AGO recycling proceeds via miRNA degradation (TDMD) in the cell, but in the absence of enzymes responsible for oligouridylation and degradation, the miRNA duplex may be released. As TDMD-competent mRNA targets have been observed to release the miRNA 3' tail from AGO2 (Sheu-Gruttadauria et al., 2019; Willkomm et al., 2022), there is a possible mechanistic similarity between the two processes, however, we do not have sufficient data to make any statement on this.
