It seems that, with every setback in the war against AIDS, a push forward comes just as soon. While HIV-blocking gel tenofovir was recently declared “safe but ineffective,” there is a light on the horizon: experiments on rats have produced a promising vaccine. According to Ars Technica (bold ours):
Since these broadly neutralizing antibodies are the sorts of things we want out of the vaccination process, a team of labs at Caltech and UCLA decided to short-circuit the need for a vaccination, or even antibody-producing immune cells. They created a disarmed adenovirus that contained the genes needed to produce a broadly effective antibody from humans, optimizing the DNA to make sure that the antibody was made in muscle cells, and then secreted into their environment.
The modified virus was then injected into mice that had had their immune systems humanized (the stem cells in their bone marrow were killed off and then repopulated with human cells). The mice were then exposed to levels of HIV many times higher than are normally present during initial infections. Not all antibodies effectively blocked new infections, but at least one did so consistently. The resistance to new HIV infections persisted for the life of the experiments.
We’re not medical experts, but that sounds pretty promising. We’d like a clarification on the wording here, though. Are they saying one of the antibodies blocked infections consistently but not effectively? Like, is this antibody the equivalent of a goalie who manages to deflect soccer balls with his fancy gloves… but they still end up bouncing into the corner of the goal nevertheless and scoring a win for the nefarious HIV team?
Other promising news in the search for a vaccine includes a possible HIV-blocking anal gel.
Photo via lu_lu’s Flickr
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TommyOC
When the reports of the gel experiments came out, people latched onto the line about the treatment not working. Taken out of context, that sounds pretty disheartening.
But the study leaders suggest one of the reasons that the gel may not have worked was because it wasn’t being taken by the study participants as directed.
There is a difference between “the study didn’t prove efficacy” versus “the medication doesn’t work.”
Hyhybt
This is good news. Of course, good news of this type is so often followed by the bad news that it doesn’t work after all… but one of these times, it will be real.
Hyhybt
@TommyOC: That’s true… like the joke about the old lady who kept a condom sitting on the reed organ in her living room.
bagooka
Let’s hope it works.
Shannon1981
I hold out hope that this epidemic will one day be a thing of the past.
MikeE
Well, I guess it’s good news for mice, then, isn’t it?
UCLAGeneticGradStudent
Clarification: Various broad-based antibodies that were considered to potentially thwart HIV infection were injected into the rats. Most of the antibodies weren’t consistently effective, with the exception of one. To continue the soccer analogy, we had many goalies at the net, but only one of them consistently blocked infection.
We’ve tried many times in the past to vaccinate individuals (traditional vaccination compels the body to produce the antibodies itself through normal immune cells), but what’s unique about this approach is that the antibody-producing genes themselves were injected (with an adenovirus) directly into muscle cells. Injecting it into muscle cells with the harmless adenovirus effectively spreads the antibodies throughout the body. Translation: this approach skips a step normally taken in the vaccination process (which has failed so far) and has the potential to be more effective.
The lab has already requested approval to move on to human testing, which may being as early as late 2012. Very exciting things to come!
Yellow belly
@MikeE: For humans, too.
B
Re No. 7 · UCLAGeneticGradStudent
Do you have any details on the following news articles: http://www.networkworld.com/community/node/79333 and http://www.itproportal.com/2011/12/05/microsoft-researchers-work-end-spamming-cure-hiv-virus/ (it seems algorithms to detect spam, which continually
“mutate” as spammers try to defeat spam filters, are being applied in HIV research.
.
UCLAGeneticGradStudent
@B:
Yeah, that’s pretty interesting. I have a friend at Washington who is a PhD in Math and is also a hard-core gamer. He was part of this study that used humans to predict the molecular structure of a protein in a retrovirus. Protein folding is incredibly complex with an almost infinite number of structural variations. That is why even the most advanced algorithm systems(i.e. computers) do a poor job of predicting the structure, as there are so many possibilities. Furthermore, viruses don’t normally evolve in the most efficient ways (which is what computers usually predict) and gamers are much better at this using their gut instincts. Why exactly I don’t know. My friend’s group took about a month to predict the molecular structure whereas it took scientists years to do so.
I’m guessing that these spammers are being used in a similar fashion as the HIV virus constantly evolves to avoid any potentially disabling agents (which is why HAART medications must be used consistently to avoid HIV resistant strains from dominating). When HIV, or any virus, mutates it’s almost impossible to predict exactly how it will alter itself. This is also why we haven’t figured out a cure to the common cold: it changes much too quickly and unpredictably.
@MikeE: The rats used were constituted with human cells. They essentially went through a bone marrow transplant destroying their natural ones and were replaced with human ones to give a more comparable system.
B
No. 10 · UCLAGeneticGradStudent wrote, “Furthermore, viruses don’t normally evolve in the most efficient ways (which is what computers usually predict) and gamers are much better at this using their gut instincts. Why exactly I don’t know. My friend’s group took about a month to predict the molecular structure whereas it took scientists years to do so.”
The programs are probably using optimization algorithms to estimate how the virus’ evolve.
If you want some technical articles, try “The challenge of designing scientific discovery games” FDG ’10 Proceedings of the Fifth International Conference on the Foundations of Digital Games.
Also, http://arstechnica.com/science/news/2011/11/gamers-create-recipes-for-protein-folding-algorithms.ars has a not-very-technical article about a game called FoldIt. One thing that helped the gamers was that the game (web based, I guess) made it possible for gamers to share their experiences and learn from each other.
Now people are trying to use machine-learning techniques to figure out how to get a computer to do the same thing.
I’ve made a guess that we’ll make enormous progress on HIV in roughly 5 years (5 to 10), mainly because of the technical improvements that let us try things so much more rapidly
today than in the past. Also, we are getting closer to the point where we can run realistic models of how a virus operates due to increases in computer speed and the amount of memory they have. Testing drugs in a computer model to find likely candidates
for real tests could speed up the process enormously.
What’s your opinion?
UCLAGeneticGradStudent
@B:
The idea of computer models predicting good research routes is still relatively new. This is more computer science related, so I honestly can’t speak with much knowledge about it. I’m assuming computer models will eventually have that breakthrough, I just haven’t seen it yet (at least in HIV research) so am a bit cautious about it.
In terms of vaccination research, I’m also fairly cautious. HIV is so unlike anything we have successfully vaccinated against. It’s incredibly variable and it attaches to the very cells that would normally fight it. Furthermore, vaccines normally compel the body to produce antibodies that are known to fight against it. This is typically discovered through individuals who have immunity/successfully fought against it (like polio or smallpox) and we could cultivate such protective antibodies. There really is no such thing in HIV. Those individuals that can naturally control the virus can do so through their DNA–not antibodies. Those individuals have a genetic mutation in their alleles that render HIV unable to enter their cells. BUT, lookout for more advancement in the next couple months regarding antibodies that ARE effective. A lot of researchers (including some profs here) have been parsing through millions of potential antibodies and some new isolations are promising!
I may be biased because of my past involvement, but I personally think that gene therapy will make the most headway the quickest. Incredibly, we appear to have the ability to filter human blood and essentially artificially manufacture the aforementioned genetic mutation. One CA company in particular is in a Stage 3 of a clinical trial that has successfully done so in HIV patients and initial results are incredibly promising. Issues of sustainability and continued production of mutated cells are the biggest question marks, but after a year it appears to be panning out.
Like you, I’m fairly optimistic. I have little doubt that a functional solution to HIV through gene therapy will be presented within 5 years, and available by 10. Unfortunately, this type of therapy isn’t ideal because access to it would be limited. BUT with the continued advancement in computer science and vaccination studies, there will hopefully be a more practical solution coming as well. Regardless, it’s amazing that there are many routes that are attacking the problem.
MikeE
as interesting as all this science talk is, IT WAS A JOKE!
jeese.
B
No. 12 · UCLAGeneticGradStudent “@B: The idea of computer models predicting good research routes is still relatively new. This is more computer science related, so I honestly can’t speak with much knowledge about it. I’m assuming computer models will eventually have that breakthrough, I just haven’t seen it yet (at least in HIV research) so am a bit cautious about it.”
In principle we know how to model how an HIV virus works and how the proteins on its surface are arranged and what type they are. The problem is that doing it from first principles (e.g., quantum mechanics and electromagnetism) is intractable – each electron adds three spacial dimensions + two spin states to the wave function, so you run out of
processing speed and memory very quickly. Fortunately, there are approximations that work pretty well, which reduces the level of intractability. Meanwhile, computer speeds have been doubling every couple of years, with similar increases in memory. If that continues sufficiently, we should eventually get machines that are up to the task.
It isn’t surprising that you haven’t seen much yet – we aren’t at the point where computers, or at least affordable ones, are fast enough with enough memory. There’s
a lot of interest in building such machines, however, and biology is only one of
many fields that would benefit from it.