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Immunology with numbers


Ramblings of a numerate immunologist


On the spread of viruses : the enemy within.

By regfbec, on 13 April 2015

I hope all readers saw our recent paper in PLOS Computational Biology  where we explored the parallels between spread of HIV within the body , which uses a combination of cell-to-cell and cell-blood-cell transmission and the spread of computer worms, some of which use a combination of local neighbourhood and remote probing to achieve maximal efficiency and persistence. Here I would like to extend the discussion of these results to a more speculative level than is generally allowed in the confines of rigorous academic peer review. I apologise that this discussion is light on quantitative analysis, contrary to the spirit of the blog. But perhaps someone can propose some quantitative way to address the questions I raise below.


The first question I would like to pose is from the perspective of HIV. What advantage, from an evolutionary perspective, is provided by dual spreading modes for the virus ? There is clearly a substantial cost to the virus involved in producing high levels of secreted virions, the vast majority of which die within 20-60 minutes without infecting another cell.

One hypothesis might be to suggest that it allows more rapid circulation of the virus and hence access to a larger reservoir of susceptible cells. Migrating  cells routinely encounter hundreds, or even thousands of other T cells per hour [1,2] ) . Infected cells, however, may migrate much more slowly [3]. Furthermore activated proliferating T cells, which provide by far the most effective targets of infection, may also migrate much more slowly, and remain attached to their cognate antigen presenting cell for much of their susceptible period [3].  Nevertheless, the extent of T cell recirculation makes this hypothesis less attractive.

An alternative hypothesis to explain the evolutionary advantage of hybrid spreading might be that cell free virus is transmitted from host to host much more efficiently than cell-associated virus, since the half-life of transferred cells in an allogeneic host is likely to be in the order of minutes, and may be too short to allow the establishment of the cellular synapse which is required for cell-cell transmission.  An instructive comparison is to compare HIV-1 with HTLV-1, another human retrovirus. HTLV-1 has been shown to spread almost exclusively by cell-cell transmission [4], and virus in blood is generally at undetectable levels. Although the prevalence of HTLV-1 in some endemic areas is very high, the virus has an ancient history in humans, and is accompanied by a relatively indolent pathology. The virus has therefor had plenty of time to establish itself in its host population. Certainly, there is no evidence for the remarkably rapid pandemic which has characterised the spread of HIV within the last 50 years. Comparison to other viruses would surely be instructive. I am not aware of what other viruses might use two parallel modes of spread, and would love to hear of any examples.

The second question is from the point of view of computer virus security. A key component of our analysis, which is explored in more detail in two other companion papers (http://arxiv.org/abs/1409.7291; http://arxiv.org/abs/1406.6046) is that the spread of computer malaware within a local network environment, is much more efficient and rapid than spread between one local network and another. We did not investigate the reasons for this behaviour in detail, but plausibly the major block to spread of the virus are institutional firewalls and once these have been penetrated the ability to infect another virus within the same system is much greater. A corollary of this phenomenon is that the ability to discriminate and suppress viruses or worms within an organisation may be as important, or even more important, than preventing the original security breach in the first place. Strategies for identifying and decommissioning malaware spread within a local network (“neighbourhood watch” approaches ) poses formidable challenges. But such strategies do start with the advantage that the set of potential sources and targets of infection are limited in number and known in advance. And useful solutions could be of major benefit to preventing the catastrophic results of cybercrime even if the primary infection event itself cannot always be prevented.

  1. Munoz MA, Biro M, Weninger W. T cell migration in intact lymph nodes in vivo. Curr Opin Cell Biol. 2014;30: 17–24. doi:10.1016/j.ceb.2014.05.002
  2. Gadhamsetty S, Marée AFM, Beltman JB, de Boer RJ. A general functional response of cytotoxic T lymphocyte-mediated killing of target cells. Biophys J. 2014;106: 1780–91. doi:10.1016/j.bpj.2014.01.048
  3. Murooka TT, Deruaz M, Marangoni F, Vrbanac VD, Seung E, von Andrian UH, et al. HIV-infected T cells are migratory vehicles for viral dissemination. Nature. Nature Publishing Group; 2012;490: 283–7. doi:10.1038/nature11398
  4. Pique C, Jones KS. Pathways of cell-cell transmission of HTLV-1. Front Microbiol. 2012;3: 378. doi:10.3389/fmicb.2012.00378


2 Responses to “On the spread of viruses : the enemy within.”

  • 1
    Changwang Zhang wrote on 13 April 2015:

    Some believes that producing large amount of short lived virions enables the virus to evolve in an unprecedented pace. The virus can then maintain a high level of genetic diversity so as to evade the immune detection.

    Similar to the computer worms, I feel survivability might be as important as if not more important than infectivity for HIV. A virus might evolve to be less infectious but more stubborn.

    There are some reports about HIV is becoming less infectious. I guess, In the long term, under the natural selection pressure, the fittest HIV variant might be able to co-exist with human without causing harm?

  • 2
    Dr. Arroyo wrote on 1 May 2015:

    Indeed, there are some studies showing a trend to less letality/infectivity in some african populations where ART access is still a challenge and rules of “natural ” selection apply sweetly. However, in industrial countries, the trend semms to go in the opposite direction, since the higher the viremia gets during the time without treatment, the easier it is for the virus to infect new individuals (another reason to start treatment as early as possible). So, the component of population genetics would also be interesting to analyze in these mathmodelcal models.

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