Decision letter | Cell-to-cell infection by HIV contributes over half of virus infection

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Cell-to-cell infection by HIV contributes over half of virus infection

Decision letter

Affiliation details

Kyushu University, Japan; Japan Science and Technology Agency, Japan; Kyoto University, Japan; University of Tokyo, Japan; Hospital Saint Louis, France; Université Paris Diderot, Sorbonne Paris Cité, France; Tokyo University of Agriculture, Japan
Arup K Chakraborty, Reviewing editor, Massachusetts Institute of Technology, United States

eLife posts the editorial decision letter and author response on a selection of the published articles (subject to the approval of the authors). An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent (see review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.

Thank you for submitting your work entitled “Cell-to-cell infection by HIV contributes over half of virus infection” for peer review at eLife. Your submission has been favorably evaluated by Naama Barkai (Senior Editor), a Reviewing Editor, and two reviewers. One of the two reviewers, Vitaly Ganusov, has agreed to share his identity.

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

While others have previously shown that cell-to-cell spread is a rapid and efficient form of infection, the novelty of this work is in its attempt to quantify the contributions of cell-to-cell spread and cell-free infection in the same culture. However, there are three major concerns about the connections between the experiments and assumptions made in the modeling that need to be addressed in order to ascertain that the conclusions are correct. These major concerns are:

1) The parameter, ω, which measures the infection rate by cell-to-cell spread is obtained by fitting the model to data, and it is assumed that ω=0 in the experiments with shaking. β, the cell-free infection rate, is assumed to be the same under both infection conditions. In the data, shaking reduces infection, consistent with decreased cell-to-cell spread. However, it is also consistent with several other possibilities. For example, reduction of both cell-to-cell spread and cell-free infection due to many possible factors including lower production rates or infectivity of virus. If this is true, a similar attenuation of viral dynamics would be observed upon shaking but for a completely different reason, and invalidate the assumptions made to fit the data. To prove that the attenuated viral dynamics are strictly the result of a loss of cell-to-cell spread, a control experiment is needed. It is up to you to choose the appropriate control experiment that establishes this. We think that the following experiment might be appropriate:

Produce cell-free virus by filtering out any cells, then add it to either shaking or static Jurkat cell cultures and measure the percent infected cells under each condition at a few time points before two days (i.e. before the second cycle of infection). If shaking only affects cell-to-cell transmission, the results should be identical for shaken or static cultures in this experiment.

2) The parameter values are taken to be constant in time, but this may not be the case. Consider the parameter g, as an example. Cells that reach a maximum density may go into growth arrest and there is a lag time to get them out of it. This would mean that g is not constant. Is there experimental evidence that the parameters do not change with time. Also, at high levels of infection, which appears to be true in the experiments, is the cell culture still stable? If not, g would not be a constant.

3) It seems that the simulations are carried out without virus removal (without c) for 24 hours, and then an instantaneous removal occurs at 90% (not continuous removal of the virus as 2.3 per day). This set-up does not seem congruent with the experiments. The simulations should be carried out in a similar way to the experimental set-up to make sure that the parameter values are properly estimated. In addition, is it certain that cells/infected cells are not removed in the experiments, as it seems is assumed in the model? Finally, more quantitative estimates of agreement between the fitted models and experimental data are required. For example, by visual inspection of Figure 2, one could argue that the model does not describe the loss of infected cells and the virus after the peak well (Figure 2A), and in Figure 2B, it is not clear how good the fits are. Error bars need to be provided for the estimated parameters in Table 1.

[Editors' note: further revisions were requested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled “Cell-to-cell infection by HIV contributes over half of virus infection” for further consideration at eLife. Your revised article has been favorably evaluated by Naama Barkai (Senior Editor), a Reviewing Editor, and one of the original reviewers. The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below:

We have read your response and revised manuscript, and believe that you have not addressed the first major and essential point. As discussed in the first report, the assumption you make is that shaking eliminates cell-to-cell spread but does not affect cell-free infection. The premise of the whole paper is based on this assumption. According to the data presented in Figure 2, this may not be the case: Day 0 infection as shown in the middle panels of Figure 2A (static) and Figure 2B (shaking) is strictly the result of cell-free infection, as you indicate in the Methods. In Figure 2A (static), the number of cell infected is between 103 to 104/ml. In Figure 2B (shaking), the number of infected cells – by what is supposed to be the same cell-free infection input according to the methods – seems to be undetectable at day 0, with the first measurements appearing at a later time. This indicates that shaking, at least as performed by the method used in this paper, decreases cell-free infection. We requested that you perform a control experiment to show that this is not the case, and that shaking does not affect cell-free infection. We had also suggested a simple experiment for you to consider: add cell-free virus to static and shaking cultures and show that the infection rate is unaffected by shaking at the first infection cycle (subsequent cycles would involve cell-to-cell spread due to the co-culture, and would not be relevant). Rather than carry out this (or some other) control experiment, you point to a past paper that showed this. But, given the data in Figure 2 (see above), it is unclear that the assumption that shaking does not affect cell free infection is correct in your experiment. Since the rest of the work presented in the paper relies on this assumption, a control experiment demonstrating this assumption to be true is necessary.

DOI: http://dx.doi.org/10.7554/eLife.08150.015