1. Microbiology and Infectious Disease
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Efficient support of virus-like particle assembly by the HIV-1 packaging signal

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Cite this article as: eLife 2018;7:e38438 doi: 10.7554/eLife.38438

Abstract

The principal structural component of a retrovirus particle is the Gag protein. Retroviral genomic RNAs contain a ‘packaging signal’ (‘Ψ') and are packaged in virus particles with very high selectivity. However, if no genomic RNA is present, Gag assembles into particles containing cellular mRNA molecules. The mechanism by which genomic RNA is normally selected during virus assembly is not understood. We previously reported (Comas-Garcia et al., 2017) that at physiological ionic strength, recombinant HIV-1 Gag binds with similar affinities to RNAs with or without Ψ, and proposed that genomic RNA is selectively packaged because binding to Ψ initiates particle assembly more efficiently than other RNAs. We now present data directly supporting this hypothesis. We also show that one or more short stretches of unpaired G residues are important elements of Ψ; Ψ may not be localized to a single structural element, but is probably distributed over >100 bases.

https://doi.org/10.7554/eLife.38438.001

Introduction

A retrovirus particle is assembled from ~1500–3000 molecules of the Gag protein, together with RNA (Vogt and Simon, 1999), as well as smaller amounts of other viral and cellular proteins and a surrounding lipid bilayer. In a cell infected with wild-type virus, the vast majority of the released particles contain the genomic RNA (gRNA) of the virus, despite the fact that this RNA is only a minor species in the virus-producing cell (Chen et al., 2009). The selection of the gRNA for encapsidation depends upon the presence in this RNA of the ‘packaging signal’ or ‘Ψ', a region of ~200 or more bases near the 5’ end of the viral RNA (Aldovini and Young, 1990; Berkowitz et al., 1996; Comas-Garcia et al., 2016; D'Souza and Summers, 2005). However, the nature of Ψ and the mechanism of selective packaging of gRNA are not well understood as yet.

In mammalian cells expressing Gag in the absence of Ψ-containing RNA, the protein assembles into virus-like particles (VLPs) structurally indistinguishable from immature virions; these particles contain roughly the same amount of RNA as wild-type particles, but this RNA is a nearly random sample of cellular mRNA molecules (Rulli et al., 2007). Similarly, recombinant Gag protein can assemble into VLPs in a defined system in vitro; while this assembly requires the presence of RNA (or DNA), virtually any single-stranded nucleic acid can support assembly under these conditions (Campbell et al., 2001; Campbell and Rein, 1999).

In an effort to understand the selective packaging of Ψ-containing RNA, we recently measured the affinity of recombinant HIV-1 Gag protein (lacking the p6 domain at its C-terminus) for different RNAs (Comas-Garcia et al., 2017). We found that the protein has similar, very high affinities for all the RNAs tested when assayed at near-physiological ionic strengths. However, further examination showed that this affinity is the sum of both specific and non-specific interactions. Non-specific binding could be selectively reduced by mutating specific residues in the protein; or by adding a vast excess of an irrelevant competitor RNA; or simply by raising the ionic strength in the assay. When the binding measurements were modified in any of these ways, a strong specific interaction with Ψ could be detected. The salt-resistance of the binding of Gag to Ψ had previously been observed, using somewhat different techniques, by Webb et al. (Webb et al., 2013).

To explain how Ψ-containing RNAs are selectively packaged, despite the fact that Gag binds any RNA tightly at physiological ionic strength and any RNA can support assembly, we proposed that binding to Ψ leads to initiation of assembly more efficiently than binding to other RNAs (Comas-Garcia et al., 2016; Nikolaitchik et al., 2013). We now present in vitro data that lend strong support to this hypothesis. This work also includes a preliminary characterization of the RNA sequences that are specifically bound by Gag under the modified assay conditions described above.

Gag has been suggested to bind specifically to several distinct sites in the 5’ region of HIV-1 RNA (Lever, 2007). These include an internal loop and surrounding bases in stem-loop 1, the locus of the ‘kissing interaction’ where dimerization of gRNA is initiated (Abd El-Wahab et al., 2014); stem-loop 2 (Amarasinghe et al., 2000); stem-loop 3 (sometimes called ‘Ψ') (De Guzman et al., 1998); and a series of very short unpaired stretches, each with one or more unpaired G residues, collectively termed the ‘Nucleocapsid Interaction Domain’ (Wilkinson et al., 2008). We tested several of these possibilities by introducing mutations into a ‘Ψ' construct and testing the binding of Gag under different conditions.

Results and discussion

One important unresolved question is the exact sequence(s) which define Ψ. We measured binding affinities using, where not specified otherwise, the methodologies described earlier (Comas-Garcia et al., 2017), except that the RNAs were 401 bases in length rather than 190 nts. These RNAs begin at either nt 150 or nt 200 (see Figure 1A) and were labeled at their 3’ ends with Cy5. As indicated in the Figure, the mutants included individual deletions spanning either stem-loop 1 or stem-loop 3, and the ‘Multiple Binding Site Mutant’ (MBSM), in which all of the G’s in the stretches identified by Wilkinson et al. as the Nucleocapsid Interaction Domain (Wilkinson et al., 2008) were replaced with A’s. We also noted that these RNAs contain a run of unpaired G and C residues (nt 442–459) that may well be paired in full-length RNA, but not in our 401-base RNAs. To test the possibility that these bases contribute to specific binding of Gag to the transcripts, we also mutated these residues to A’s, both in the otherwise wild-type construct beginning at nt 200 (creating the ‘GC loop mutant’) and in the MBSM; this construct is designated ‘MBSM second generation’. In all cases, removal of bases by deletion was compensated by extending the 3’ end of the RNA, so that all the RNAs were 401 bases long. As a negative control RNA, we produced the reverse complement of Ψ, that is RNA complementary to nt 200–600.

Schematic representation of the tested RNAs and their binding profiles to Gag measured by Cy5 quenching.

(A) Schematic representation of the expected secondary structure of the RNAs used in these experiments. These representations are based on the secondary structure proposed by Wilkinson and co-workers (Wilkinson et al., 2008). The purple stars in the MBSM first and second generation and the GC loop mutant RNAs indicate mutations of G to A, while the blue stars represent C to A mutations. (B) Binding curves for all of the tested RNAs with Δp6 Gag at 200 mM NaCl, monitored by quenching as previously described (Comas-Garcia et al., 2017). The buffer in this assay contained 0.2M NaCl, 20 mM Tris-HCl pH 7.5, 5 mM MgCl2, 1 µM ZnCl2, 0.1 mM PMSF, 1 mM β-mercaptoethanol, and 0.05%(v/v) Tween 20. (C) Binding curves obtained as in (B), but in the presence of a 50-fold excess by mass of yeast tRNA. (D) Binding curves obtained as in (B), but in a buffer containing 400 mM, rather than 200 mM, NaCl. Values in (B–D) are means of two independent experiments, and each point in each experiment is the mean of 10 measurements. Experiments giving KD values differing by >10% from the consensus values were discarded.

https://doi.org/10.7554/eLife.38438.002

To test the effects of these changes upon the specific and non-specific binding by Gag, we titrated Gag into these RNAs, monitoring binding by the quenching of the fluorophore as described (Comas-Garcia et al., 2017), either in binding buffer (containing 0.2M NaCl), or in binding buffer with a 50-fold excess by mass of yeast tRNA, or in binding buffer containing 0.4M NaCl. Results of these assays are shown in Figures 1B, C and D, respectively. It is evident that Gag binds all the tested RNAs well in binding buffer. However, addition of yeast tRNA (Figure 1C) or raising the ionic strength in the assay (Figure 1D) strongly depressed binding to both iterations of the MBSM RNA, while deleting either SL1 or SL3 did not. Binding to the reverse complement RNA was drastically reduced under both of these conditions. These results show that the specific binding of Gag to Ψ, detected in these assays, depends upon some or all of the clusters of unpaired G residues called the Nucleocapsid Interaction Domain (Wilkinson et al., 2008), but neither stem-loop one nor stem-loop three is crucial for this binding (Figure 1C and D). A similar mutant has been reported to be deficient in selective packaging in vivo (Keane et al., 2015).

As discussed above, we have proposed that genomic RNA is selectively packaged because binding to Ψ is particularly efficient at initiating VLP assembly (Comas-Garcia et al., 2016). Thus, it was of interest to assess the abilities of the different RNAs to support VLP assembly. For these experiments we focused on the Ψ that starts at nt 200, the MBSM second generation and the Reverse complement RNA. Also, for these experiments on particle assembly, we used Gag protein lacking most of the matrix (MA) domain, as well as p6: we have previously reported that Δp6 assembles into VLPs with radii of curvature drastically different from those of authentic virions (Campbell and Rein, 1999), indicating that they are quite different in overall structure from authentic immature particles. In contrast, the deleted protein (‘Δ16–99 Gag’, also frequently called ‘ΔMA’) assembles into VLPs in which the lattice of proteins closely mimics that in immature HIV-1 virions (Campbell et al., 2001; Briggs et al., 2009; Fäcke et al., 1993; Gross et al., 2000; Wilk et al., 2001).

We first compared the binding to RNA of Δ16–99 Gag with that of Gag. Our previous measurements monitored RNA-binding using the ability of Gag to quench the Cy5 fluorophore on the RNA (Comas-Garcia et al., 2017). However, we found that Δ16–99 Gag does not quench the fluorophore; evidently, the quenching involves the MA domain. Therefore, we used microscale thermophoresis (MST) for monitoring binding by this protein. As shown in Figure 2A, MST and quenching measurements give very similar results for the binding of Δp6 Gag to the Ψ RNA that starts at nt 200; at 0.15 M NaCl the KDs for MST and FCS were 14 and 17 nM, respectively, while at 0.45 M NaCl they were 256 and 302 nM. In all cases the Hill coefficient was greater than 1.0. These data show that MST is able to recapitulate our original FCS results (Comas-Garcia et al., 2017). MST data are presented in more detail in Figure 2—figure supplement 1 and Table 1. Interestingly, Δ16–99 Gag bound relatively weakly to all 3 RNAs at 0.5M NaCl (see Table 1). The implications of this result are now under further investigation.

Table 1
Results of MST measurements of binding of Δ16-99 Gag to RNAs at 0.15 and 0.5M NaCl.

The Table shows means and standard deviations of replicate measurements.

https://doi.org/10.7554/eLife.38438.003
RNA (0.15M NaCl)Kd (nM)ErrornHError
Ψ200645163.20.2
MBSM 2nd gen737173.50.3
Rev Comp1042422.50.2
RNA (0.5M NaCl)
Ψ2009452671.40.1
MBSM 2nd gen22001511.10.1
Rev Comp24791091.30.1
Figure 2 with 1 supplement see all
Comparison of RNA-Gag binding measurements by Cy5 quenching and Microscale Thermophoresis (MST).

(A) Comparison of FCS (i.e. Cy5 quenching in FCS apparatus) and MST methods for measurement of binding of Δp6 Gag to dimeric Ψ 200 RNA. The Cy5-tagged RNA was dimerized as described (Comas-Garcia et al., 2017) and diluted into binding buffer B to a concentration of 7 nM. This buffer was composed of 50 mM phosphate, pH 7.0, 0.05% Tween 20, 0.1 mM PMSF, and 1 mM β-mercaptoethanol, together with either 0.15 M or 0.45 M NaCl. The sample was then divided and, after 16 hr at 4°C, used for binding measurements by FCS or MST. Both methods give very similar KDs, although the MST curves suggest somewhat higher cooperativity in the binding than FCS. (B) Binding of Δ16–99 Gag protein to the three RNAs used for the Virus-like-particle (VLP) assembly experiments. Ψ 150 RNA, MBSM second generation RNA, and Reverse Complement RNA were all treated as described (Comas-Garcia et al., 2017) for Ψ dimerization. They were then diluted into Assembly Buffer (20 mM Tris pH 7.5, 0.15M NaCl, 5 mM MgCl2, 1 µM ZnCl2, 0.1% Tween 20, 0.1 mM PMSF, and 1 mM DTT). Binding of Δ16–99 Gag to the RNAs was then measured by MST. The FCS data in Figure 2A was treated as in Figure 1B–D. All MST data results are the means of three independent experiments. Each data-point in each MST experiment is the mean of triplicate measurements.

https://doi.org/10.7554/eLife.38438.004

We wished to quantitatively compare the different RNAs with respect to their ability to support assembly. It was important that all of the RNA be bound by the Δ16–99 Gag protein in these experiments, so that any differences observed represent differences in support of assembly, not differences in the extent of binding. Figure 2B shows the results of MST binding assays in a buffer closely resembling that used in assembly experiments, yielding KDs of 226, 382, and 568 nM for Ψ (beginning at nt 200), MBSM second Generation (Gen), and Reverse Complement (Rev Comp) RNAs, respectively. Specifically, it is evident that nearly all of each RNA is bound at 1–2 µM Δ16–99 Gag, significantly below the levels used in the assembly experiments (see Figure 3 below).

Assembly of Δ16–99 Gag protein on different RNAs.

Cy5-tagged Ψ 200 RNA (panel A), MBSM second generation RNA (panel B), and Reverse Complement RNA (panel C) were all treated as in the ‘RNA Dimerization’ protocol (Comas-Garcia et al., 2017). They were then diluted to 61 nM in Assembly Buffer and Δ16–99 Gag was titrated into these solutions. After 6 hr at 4°C, the mixtures were layered on 5–50% (w/v) sucrose gradients. The gradients had the same composition as Assembly Buffer except that they did not contain Tween 20, β-mercaptoethanol, or PMSF. After centrifugation for 14 hr at 76,000 x g, fractions were collected from top to bottom and assayed for Cy5 fluorescence and for Gag protein content by spotting aliquots onto nitrocellulose membrane and immunoblotting with anti-p24CA antiserum. The points are means and standard deviations of 3 independent experiments; experiments were excluded if the positions of the peaks were different from these consensus profiles.

https://doi.org/10.7554/eLife.38438.006

Finally, we compared different RNAs with respect to their ability to support assembly of Δ16–99 Gag into VLPs. Different amounts of Δ16–99 Gag were added to 61 nM solutions of the Cy5-labeled RNAs; VLP assembly was monitored by the shift of the RNA into large, rapidly sedimenting structures, and was confirmed by negative-stain electron microscopy (Figure 4). Although well-formed VLPs were visible in all the reactions (see insets in the Figure), a variety of other structures were also observed, particularly in the ψ and MBSM samples. The mixtures were layered onto sucrose gradients and centrifuged at 76,000 x g for 14 hr. Fractions were collected and assayed for both Cy5 fluorescence and Δ16–99 Gag protein content (p24CA signal). Results of this experiment for Ψ, MBSM second Gen, and Rev Comp RNAs are shown in Figure 3A–C. In each panel, the black line is the sedimentation profile of the free RNA. In Figure 3A, the free Ψ RNA is a single peak centered on fraction 6. Addition of 3 μM Δ16–99 Gag (red curve) shifts the majority of this RNA to fraction 8, with a significant tail extending nearly to the bottom of the gradient. When 7.5 μM or higher concentrations of Δ16–99 Gag are added, nearly all the RNA is shifted to a broad peak centered around fraction 13. Qualitatively similar results were obtained with MBSM second Gen (Figure 3B) and Rev Comp (Figure 3C) RNAs.

Negative stain electron micrographs on aliquots from the assembly reactions in (A-C).

Insets: well-formed VLPs at higher magnification.

https://doi.org/10.7554/eLife.38438.007

We also determined the distribution of the Δ16–99 Gag protein in these gradients, by performing immunoblotting on dot blots of aliquots of the gradient fractions (Figure 5). We found that in all cases, the vast majority of the protein remained near the top of the gradient (fractions 2–4), and the presence of 61 nM RNA had little or no significant effect upon the distribution of the protein. The fact that the overall protein profile was not significantly affected by the presence of the RNA is not surprising, as the protein was in 50-fold molar excess over the RNA in these gradients.

Distribution of Δ16–99 Gag in the gradients in Figure 3A–C.

Aliquots of the gradient fractions were spotted on membranes and treated as in immunoblotting. A parallel dilution series showed that the measurements were within the linear range of the assay. The values are the means of two independent experiments.

https://doi.org/10.7554/eLife.38438.008

In order to quantitatively assess the level of VLP assembly in each of the reactions, we summed the amount of RNA between fractions 10 and 18. The results of this analysis are shown in Figure 6. These data were fitted, using the non-linear least squares Levenberg-Marquardt method, using the equation

Quantitative comparison of the ability of dimeric HIV Ψ 200, MBSM second generation, and Reverse Complement RNAs to support VLP assembly.

RNA in fractions 10–18 in Figure 3(A–C is summed and plotted vs. the concentration of Δ16–99 Gag protein in the assembly reaction. The points are fitted with a cooperative model.

https://doi.org/10.7554/eLife.38438.009
Yx=11+KXn

where x is the protein concentration, Y(x) is the fraction of RNA in the bottom half of the tube, and n is a fitting parameter. This equation is analogous to the Hill cooperative model for macromolecular association. Solving for these values yielded the results shown in Table 2.

Table 2
K and n values and their errors from data shown in Figure 6.
https://doi.org/10.7554/eLife.38438.010
SampleK (μM)Error (μM)NError
 HIV Ψ 2003.74±0.561.2±0.2
 MBSM 2nd Gen9.34±0.581.0±0.1
 Rev Comp9.94±0.421.3±0.1

The results reveal a striking difference between Ψ RNA and either MBSM second Gen or Rev Comp RNA: particularly at the lower protein levels, Ψ supports assembly far more efficiently than the other RNAs. For example, at 11.25 μM Δ16–99 Gag, approximately ⅘ of the Ψ RNA has been shifted into the bottom half of the gradient, while only about half of the MBSM second Gen or Rev Comp RNA has undergone a similar shift.

These results are in complete concordance with our hypothesis that binding to a packaging signal nucleates assembly with particularly high efficiency (Comas-Garcia et al., 2016; Nikolaitchik et al., 2013). Simulations by Perlmutter and Hagan (Perlmutter and Hagan, 2015) also demonstrate the quantitative plausibility of this hypothesis. The fact that when Gag is limiting, there is more assembly on Ψ than on other RNAs (shown here in a defined system in vitro), has also been demonstrated in vivo (Dilley et al., 2017); our finding that the same result is obtained in a defined in vitro system shows that this is a direct reflection of the interactions between Gag and the RNAs, and that other cellular components do not drive this phenomenon to any significant degree. The second important finding presented here is that the unpaired guanines within the first few hundred bases of HIV-1 RNA make a major contribution to the specific interactions between Gag and Ψ, as manifested in direct binding assays (Figure 1). In fact, the contribution of these clusters of unpaired bases is far more important than that of either SL1 or SL3. Somewhat similar data have been reported by Webb et al. (Webb et al., 2013). Furthermore, these unpaired bases are critical for efficient VLP assembly, under conditions in which the protein binds equally well to all the RNAs tested (Figures 3,6). Altogether, these results support our hypothesis that Ψ promotes selective packaging of the HIV-1 genomic RNA by virtue of its distinctive efficiency in promoting particle assembly. The data suggest that binding to Ψ reduces the activation energy of the assembly process. We believe that this phenomenon explains the selective packaging of gRNA, in preference to other, cellular RNAs, into virions in infected cells. Experiments to identify a hypothetical nucleating complex are now under way.

Materials and methods

Key resources table
Reagent type
(species) or resource
DesignationSource or referenceIdentifiersAdditional information
Recombinant DNA reagentΔp6 Gag
expression plasmid
PMID 9971810
Recombinant DNA reagentΔ16–99
Gag expression plasmid
PMID 10619849
OtherΨ150 RNAGenBank: AF324493.2nt 150–550
OtherΨ200 RNAGenBank: AF324493.2nt 200–600
OtherΔSL1 RNAGenBank: AF324493.2nt 150–180 joined to nt 280–650
OtherΔSL3 RNAGenBank: AF324493.2nt 150–305 joined to nt 405–650
OtherMBSM first
generation RNA
GenBank: AF324493.2G224, G226, G240, G241, C243, G270,
G272, G273, C274, G275, G289, G290,
G292, G310, C312, G318, G320, G328,
G239 of Ψ200 replaced with A's
OtherMBSM second
generation RNA
GenBank: AF324493.2G442, G443, G444, C445, G448, C449,
G451, G452, G453, G455, C456, G459
of MBSM 1 st generation replaced
with A's
OtherGC loop mutant RNAGenBank: AF324493.2G442, G443, G444, C445, G448, C449,
G451, G452, G453, G455, C456, G459
of Ψ200 replaced with A's
OtherReverse
Complement RNA
GenBank: AF324493.2RNA is complementary to Ψ150

Except where otherwise specified, all procedures were as previously described (Comas-Garcia et al., 2017). RNAs were produced by in vitro transcription of linearized plasmids containing the T7 promoter. All transcripts were 401 nucleotides long unless indicated otherwise and were ultimately derived from the pNL4-3 molecular clone of HIV-1. Numbering begins with the first nucleotide in the R region, equivalent to nt 454 in the DNA sequence. Specifically, HIV-1 Ψ 150 represents nucleotides 150–550; HIV-1 Ψ 200 contains nt 200–600; ΔSL1 contains nt 150–180 and 280–650; ΔSL3 contains nt 150–305 and 405–650; 1st-generation MBSM was derived from HIV-1 Ψ 200 by replacement of G224, G226, G240, C243, G241, G270, G272, G273, C274, G275, G289, G290, G292, G310, C312, G318, G320, G328, and G329 with adenines (Wilkinson et al., 2008). The RNA transcribed from this HIV Ψ 200-derived plasmid would still contain a highly GC-rich sequence which would quite possibly be unpaired. To eliminate this potential source of unpaired G residues, we also generated the MBSM second-generation, in which the first-generation MBSM was modified by replacing G442, G443, G444, C445, G448, C449, G451, G452, G453, G455, C456, and G459 with adenines. This latter series of changes was also produced in HIV-1 Ψ 200, yielding the ‘HIV-1 GC loop’ plasmid. In some experiments, the negative strand complementary to the HIV-1 Ψ 150 RNA (‘Reverse Complement’) was produced by transcribing a plasmid in which the T7 promoter was at the 3’ end, rather than the 5’ end, of the HIV-1 ψ 200 insert. The inserts in all plasmids were completely verified by sequencing.

MST measurements were performed in premium coated capillaries on a Monolith NT.115 instrument according to the manufacturer’s instructions (Nanotemper Technologies GmbH). Samples were incubated 20 min at 22°C after loading into measuring capillaries. All experiments were done with temperature control set to 22°C. LED power was 90% for Ψ and second generation MBSM RNAs and 50% for Reverse complement RNA. MST power was 20% for all measurements with 5 s fluorescence read before MST laser on, 20 s MST laser switched on and 5 s fluorescence read after MST laser off.

References

  1. 1
  2. 2
    Mutations of RNA and protein sequences involved in human immunodeficiency virus type 1 packaging result in production of noninfectious virus
    1. A Aldovini
    2. RA Young
    (1990)
    Journal of Virology 64:1920–1926.
  3. 3
  4. 4
    RNA packaging
    1. R Berkowitz
    2. J Fisher
    3. SP Goff
    (1996)
    Current Topics in Microbiology and Immunology 214:177–218.
    https://doi.org/10.1007/978-3-642-80145-7_6
  5. 5
  6. 6
  7. 7
    In vitro assembly properties of human immunodeficiency virus type 1 gag protein lacking the p6 domain
    1. S Campbell
    2. A Rein
    (1999)
    Journal of Virology 73:2270–2279.
  8. 8
  9. 9
  10. 10
  11. 11
  12. 12
  13. 13
  14. 14
    A large deletion in the matrix domain of the human immunodeficiency virus gag gene redirects virus particle assembly from the plasma membrane to the endoplasmic reticulum
    1. M Fäcke
    2. A Janetzko
    3. RL Shoeman
    4. HG Kräusslich
    (1993)
    Journal of Virology 67:4972–4980.
  15. 15
  16. 16
  17. 17
  18. 18
  19. 19
  20. 20
  21. 21
    Mass determination of rous sarcoma virus virions by scanning transmission electron microscopy
    1. VM Vogt
    2. MN Simon
    (1999)
    Journal of Virology 73:7050–7055.
  22. 22
  23. 23
  24. 24

Decision letter

  1. Stephen P Goff
    Reviewing Editor; Howard Hughes Medical Institute, Columbia University, United States
  2. Gisela Storz
    Senior Editor; National Institute of Child Health and Human Development, United States

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

Thank you for submitting your article "Efficient support of virus-like particle assembly by the HIV-1 packaging signal" for consideration by eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Gisela Storz as the Senior Editor. The following individual involved in review of your submission has agreed to reveal his identity: Jeremy Luban (Reviewer #3).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

This paper, submitted as a Research Advance, presents additional information about the interactions between the HIV-1 genomic RNA and Gag protein constructs. The work extends the earlier results demonstrating both specific and nonspecific RNA binding activity by Gag, and the need for either high salt or high competitor RNA concentrations to reveal the specific binding. (The earlier paper includes much more theoretical analysis of the binding, and modeling of the electrostatics involved.) Based on the earlier work, most readers might have come to the conclusion that in vivo, high competitor RNA levels were present and could have explained the high efficiency of viral RNA packaging. However, the authors here provide additional support for their proposal that the HIV-1 RNA triggers virion assembly more efficiently than other RNAs and that this explains the higher abundance of viral RNA in the final virion preps. Here the binding curves are similar to before (Figure 2). The newer part is the sedimentation of assembled Gag constructs in the presence of RNA, measuring the rapid sedimentation resulting from coassembly (Figure 3). The specific packageable RNA is shown to induce particles at lower concentration than the nonspecific RNAs, and analysis of the Hill equation for binding suggests about a three-fold lower K value. While the electron micrographs of particles are underwhelming, the RNA results (Figure 4 and Table 1) seem to confirm the claim of selective assembly. The punch line should be of interest to the community. The new RNA mutants also provide some new information about what is required for the enhanced assembly.

One reviewer had some specific issues that need to be addressed. Their review is included in its entirety below. Their points are valid and deserve as detailed a response as possible.

Reviewer #2:

The eLife manuscript by Comas-Garcia et al. is a Research Advance submission based on the previous publication of Comas-Garcia et al., entitled "Dissection of specific binding of HIV-1 Gag to the 'packaging signal' in viral RNA." The stated advances of the current manuscript are support for the hypothesis that encapsidation signal positive (Ψ+) RNAs initiate particle assembly more efficiently than other RNAs, and that unpaired G residues are important elements of the Ψ signal. The degree to which these observations are novel enough to support eLife publication, rather than publication in a more specialized journal, is a matter of question. The certainty of the results, especially as regards particle assembly initiation, also is a concern. Specific comments are as follows:

1) Figures 1 and 2A: The results concerning the potential importance of unpaired G residues to RNA binding appear reasonably solid, but have been reported in other experimental systems already (Keane et al., 2015; Rye-McCurdy et al., 2016). I also am troubled by the statement in the legend to Figure 1 that results are the means of only two independent experiments, and that "experiments giving Kd values differing by >10% from the consensus values were discarded." It would be nice to know how many such experiments were discarded, and why they were deemed inaccurate.

2) MST experiments: My understanding is that MST experiments were not performed in the initial studies. Because of this, presenting some of the raw data on controls is of interest, as would be showing results with additional RNA substrates, and giving the actual Hill coefficients.

3) Ψ+ RNA effects on assembly: The hypothesis that Ψ+ RNA triggers particle assembly is a logical one, and has received support elsewhere. With respect to the current manuscript, the proof for the hypothesis has not been explained clearly. As I understand it, the crux of the proof here is that the Ψ 2 200 RNA binds Δ16-99 Gag in assembly buffer with the same affinity as the other RNAs (Figure 2B), but partitions more efficiently into higher S value fractions when assembled with higher concentrations of Δ16-99 Gag (Figure 3). The approach and results raise some questions and concerns:

a) Why did the authors have to use Δ16-99 Gag rather than the otherwise wild type Δp6 Gag?

b) Why doesn't Δ16-99 Gag quench the fluorophore in FCS experiments?

c) The Δ16-99 Gag protein binds significantly less well to RNAs at 150 mM NaCl than the Δp6 Gag protein (Figure 2). What happens when the ionic strength is raised, or yeast RNA is added?

d) Figure 3: Please show deviations on the graphs. Please also state how many experiments were excluded because the positions of the peaks were different from the consensus profiles.

e) Figure 3—figure supplement 1: This should be in the paper. I also see lots of spots in A, things that look like tiny rods in B, and a clean background in C. The particles in C also look smaller than in A and B. Please explain.

f) Figure 3—figure supplement 2: This should be in the paper. It also would be useful to see the Gag profiles for the incubations with all the higher concentrations of Gag. It would have been nice to have seen a shift in Gag.

g) Figure 3: What happens when an excess of yeast tRNA is added?

https://doi.org/10.7554/eLife.38438.013

Author response

One reviewer had some specific issues that need to be addressed. Their review is included in its entirety below. Their points are valid and deserve as detailed a response as possible.

Reviewer #2:

The eLife manuscript by Comas-Garcia et al. is a Research Advance submission based on the previous publication of Comas-Garcia et al., entitled "Dissection of specific binding of HIV-1 Gag to the 'packaging signal' in viral RNA." The stated advances of the current manuscript are support for the hypothesis that encapsidation signal positive (Ψ +) RNAs initiate particle assembly more efficiently than other RNAs, and that unpaired G residues are important elements of the Ψ signal. The degree to which these observations are novel enough to support eLife publication, rather than publication in a more specialized journal, is a matter of question. The certainty of the results, especially as regards particle assembly initiation, also is a concern. Specific comments are as follows:

1) Figures 1 and 2A: The results concerning the potential importance of unpaired G residues to RNA binding appear reasonably solid, but have been reported in other experimental systems already (Keane et al., 2015; Rye-McCurdy et al., 2016).

The reviewer notes that previous publications have also highlighted the importance of unpaired G residues to RNA binding, as we mentioned in the original manuscript. However, we would point out that the previous studies involved binding of free NC protein (not Gag) to RNA (Keane et al., 2015) and RNA packaging in vivo (also Keane et al., 2015). We previously showed that both MA and CA domains make important contributions to RNA-binding (Comas-Garcia et al., 2017), so that binding by Gag is not equivalent to binding by NC protein. Effects on packaging in vivo could, of course, be mediated or influenced by any cellular constituent; in contrast, our results show directly that the G’s are important in the salt-resistance of the binding of Gag to Ψ and in the efficiency with which Ψ supports in vitro assembly, in the absence of any other reactants. In addition, Webb et al., 2013(this would have been a more appropriate citation than Rye-McCurdy et al., 2016 and we have now replaced that reference with Webb et al., 2013 in the revised manuscript) did report that the binding of Δp6 Gag to a Ψ construct was less salt-resistant if 12 bases, mainly G’s, were changed to A’s; this “Psi-12M” is similar to our “MBSM” RNA. While the general conclusions about binding in Webb et al. are similar to those in our Figure 1D, we would also note that Webb et al. used a different experimental approach from ours: rather than assaying binding directly at different ionic strengths, they monitored dissociation of preformed protein-RNA complexes as the ionic strength was raised. As we discussed briefly in our 2017 paper, this approach assumes a linear relationship between [Na+] and KD, and could not have detected the change in the proteins’ binding properties as the salt concentration is raised. We have now pointed out their prior results in the revised manuscript (Introduction, fourth paragraph).

I also am troubled by the statement in the legend to Figure 1 that results are the means of only two independent experiments, and that "experiments giving Kd values differing by >10% from the consensus values were discarded." It would be nice to know how many such experiments were discarded, and why they were deemed inaccurate.

The reviewer also asks about experiments that were discarded, as mentioned in the legend to Figure 1. Only two experiments were discarded. In one, an attempt to measure binding of GagΔp6 to 2nd generation MBSM RNA at 0.4M NaCl, no binding was detected, in stark contrast to other experiments. We suspect that the target RNA had been degraded. The other was a competition experiment attempting to measure binding to RevComp RNA in the presence of tRNA. This experiment was discarded because the binding curve failed to reach a plateau.

2) MST experiments: My understanding is that MST experiments were not performed in the initial studies. Because of this, presenting some of the raw data on controls is of interest, as would be showing results with additional RNA substrates, and giving the actual Hill coefficients.

The reviewer asks that more data be included on MST, which was used in the present manuscript to measure binding of protein to RNAs but was not used previously. We have added Figure 2—figure supplement 1, which presents in panels A and B, the raw MST time-trace data for binding of Δ16-99 Gag to ψ RNA in 0.15 and 0.5M NaCl; in panel C, the superimposed cross-sectional profiles of the fluorescence in the MST capillaries, where the symmetrical curves indicate that nothing is sticking to the walls of the capillaries; and in panel D, the profiles of the individual capillaries (containing RNA + different amounts of protein); the near-identity of these profiles shows that the capillaries all contained same amount of fluorescent RNA. The results of the MST measurements are now summarized in Table 1.

3) Ψ + RNA effects on assembly: The hypothesis that Ψ + RNA triggers particle assembly is a logical one, and has received support elsewhere. With respect to the current manuscript, the proof for the hypothesis has not been explained clearly. As I understand it, the crux of the proof here is that the Ψ 2 200 RNA binds Δ16-99 Gag in assembly buffer with the same affinity as the other RNAs (Figure 2B), but partitions more efficiently into higher S value fractions when assembled with higher concentrations of Δ16-99 Gag (Figure 3). The approach and results raise some questions and concerns:

a) Why did the authors have to use Δ16-99 Gag rather than the otherwise wild type Δp6 Gag?

We are sorry that we did not explain this in the original submission. We found many years ago (Campbell and Rein, 1999) that the VLPs formed when nucleic acid is added to GagΔp6 are far smaller than authentic HIV-1 virions, and thus cannot have the same architecture as authentic immature particles. In contrast, Δ16-99 Gag forms particles of the correct size in the presence of nucleic acid, and extensive studies from several labs have shown that the overall architecture of these VLPs is an excellent facsimile of that in immature particles (Campbell et al., 2001; Briggs et al., 1993; Gross et al., 2001; Wilk et al., 2001). We have added a brief explanation to the revised manuscript (Results and Discussion, third paragraph).

b) Why doesn't Δ16-99 Gag quench the fluorophore in FCS experiments?

We do not know. As we discussed in the original 2017 manuscript, the quenching of Cy5 by GagΔp6 represents stabilization of a non-fluorescent isomer of Cy5. We have also observed that free NC protein does not quench Cy5-labeled RNAs. These observations suggest that the quenching involves the MA domain in GagΔp6, but we have no further information on this. We have noted this in the fourth paragraph of the Results and Discussion.

c) The Δ16-99 Gag protein binds significantly less well to RNAs at 150 mM NaCl than the Δp6 Gag protein (Figure 2). What happens when the ionic strength is raised, or yeast RNA is added?

We are now investigating the role of the MA domain in specific and non-specific RNA-binding. We have found that the binding of Δ16-99 Gag to Ψ RNA, as well as to the control RNAs, is strongly depressed at high ionic strengths. We have not yet tested the effect of competitor tRNA. As mentioned above, we have added a supplementary figure and a Table with the MST data for binding of Δ16-99 Gag to the RNAs.

d) Figure 3: Please show deviations on the graphs. Please also state how many experiments were excluded because the positions of the peaks were different from the consensus profiles.

We have added the deviations to Figure 3 (now Figure 4) as requested by the reviewer. Two experiments were discarded because the labeled RNA barely moved from the top of the gradient. We assume that the RNA in these samples was degraded.

e) Figure 3—figure supplement 1: This should be in the paper. I also see lots of spots in A, things that look like tiny rods in B, and a clean background in C. The particles in C also look smaller than in A and B. Please explain.

The reviewer asks that the electron micrographs, which were Figure 3—figure supplement 1 in the original manuscript, be moved to the body of the paper. We have now made them Figure 3. The reviewer also asks for a little more information about what is seen in the electron micrographs. Our intention was just to demonstrate that the protein successfully assembles into VLPs under the conditions of these experiments. We have also added an inset to each of the 3 panels, presenting a VLP at higher magnification for greater clarity. Finally, the reviewer asks about the miscellaneous structures in these images which are not spherical VLPs. It is obvious that a wide variety of structures are formed and we have noted that in the revised manuscript (Results and Discussion, sixth paragraph). Finally, the reviewer mentions a “clean background” in C. We have not investigated this systematically as yet, but the reviewer may well be correct that fewer structures other than intact VLPs are formed on Reverse Complement RNA. We have noted this possibility in the aforementioned paragraph.

f) Figure 3—figure supplement 2: This should be in the paper. It also would be useful to see the Gag profiles for the incubations with all the higher concentrations of Gag. It would have been nice to have seen a shift in Gag.

The reviewer asks that Figure 3—figure supplement 2, the profile of Gag in the sucrose gradients, be included in the paper. We have now made it Figure 5. The reviewer also asks about the profiles obtained with higher Gag concentrations, where Gag is in even greater excess over the RNA. In fact the amounts of Gag here were so high that it is not trivial to obtain quantitative data on Gag in these gradients. The vast majority of Gag remains at the top of the gradient; this does not seem like useful information to us and we would prefer to omit these profiles.

g) Figure 3: What happens when an excess of yeast tRNA is added?

The reviewer asks about adding competitor RNA, such as yeast tRNA, in the assembly experiments. We agree that this is an interesting suggestion but have not tried it as yet.

https://doi.org/10.7554/eLife.38438.014

Article and author information

Author details

  1. Mauricio Comas-Garcia

    HIV Dynamics and Replication Program, Center for Cancer Research, National Cancer Institute, Frederick, United States
    Present address
    1. Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
    2. Centro de Investigaciones en Ciencias de la Salud y Biomedicina, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Investigation, Methodology, Writing—original draft, Writing—review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7733-5138
  2. Tomas Kroupa

    HIV Dynamics and Replication Program, Center for Cancer Research, National Cancer Institute, Frederick, United States
    Contribution
    Data curation, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5996-9057
  3. Siddhartha AK Datta

    HIV Dynamics and Replication Program, Center for Cancer Research, National Cancer Institute, Frederick, United States
    Contribution
    Conceptualization, Resources, Data curation, Methodology, Writing—review and editing
    Competing interests
    No competing interests declared
  4. Demetria P Harvin

    HIV Dynamics and Replication Program, Center for Cancer Research, National Cancer Institute, Frederick, United States
    Contribution
    Resources, Investigation, Methodology
    Competing interests
    No competing interests declared
  5. Wei-Shau Hu

    HIV Dynamics and Replication Program, Center for Cancer Research, National Cancer Institute, Frederick, United States
    Contribution
    Conceptualization, Investigation, Writing—review and editing
    Competing interests
    No competing interests declared
  6. Alan Rein

    HIV Dynamics and Replication Program, Center for Cancer Research, National Cancer Institute, Frederick, United States
    Contribution
    Conceptualization, Supervision, Funding acquisition, Methodology, Writing—original draft, Writing—review and editing
    For correspondence
    reina@mail.nih.gov
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8273-546X

Funding

National Cancer Institute

  • Mauricio Comas-Garcia
  • Tomas Kroupa
  • Siddhartha AK Datta
  • Demetria P Harvin
  • Wei-Shau Hu
  • Alan Rein

National Institutes of Health (Intramural AIDS Targeted Antiviral Therapy Program)

  • Mauricio Comas-Garcia
  • Alan Rein

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

This study was supported by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research, and in part with funds from the Intramural AIDS Targeted Antiviral Therapy Program. We thank Karin Musier-Forsyth and Roya Zandi for critical discussions and Sergey Tarasov and Marzena Dyba for help with MST measurements.

Senior Editor

  1. Gisela Storz, National Institute of Child Health and Human Development, United States

Reviewing Editor

  1. Stephen P Goff, Howard Hughes Medical Institute, Columbia University, United States

Publication history

  1. Received: May 21, 2018
  2. Accepted: August 1, 2018
  3. Accepted Manuscript published: August 2, 2018 (version 1)
  4. Version of Record published: August 14, 2018 (version 2)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

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