Field of Science

#microtwjc ...Just Add Manuka Honey.

I tried. I really tried to avoid blogging, and to concentrate on my thesis. When the microbiology twitter journal club appeared, I thought that I may write a piece when I had finished with my thesis.
But then, they had to go and pick a paper about Streptococcus pyogenes, and I find myself drawn back into this blog. I tend to focus on the results sections of the paper , rather than the introduction and discussion, because frankly it's the whole point of the paper.



Anyway, the title of this paper is "Manuka honey inhibits the development of Streptococcus pyogenes biofilms and causes reduced expression of two fibronectin binding proteins"
This is not really an unexpected result. Manuka honey has multiple constituents that could in fact be very useful in combating bacterial infection, such as methylglyoxal.  Honey itself has been shown to have antibacterial activity. So finding that manuka honey is antibacterial does not really surprise. But that is not where the wow factor of this paper is. I'm getting ahead of myself.
What I intend to do here is to present my thoughts on the figures they present in the paper, and the experiments that lead to their creation. I do always try to find something wrong with every paper I read (and write) and this is more of a test of how well I've read it, and not necessarily reflective of its quality. By that measure, I read this paper really well.
So , without further ado, let's dive into the paper, figure by figure.


Figure 1
They grew up the bacteria over an 8 hour period, and with every hour a sample was taken from culture and analysed for turbidity. The science behind this process is very simple, you take a tube with bacteria, shine a light (with a wavelength of 600nm) through it. Since bacteria absorb light, the more bacteria you have in the sample, the more light is absorbed.
So they grew cultures which were either 0%, 20% or 40% manuka honey, and they found that 20% was sufficient to inhibit growth, and 40% completely prevented it. I'm surprised they didn't fit their data to a logistic curve, because that would have allowed them to do some stats and come up with the statistics for growth rate and μmax.  But that isn't really necessary for them to back up their main point, which is that manuka honey inhibits growth in a stationary culture.

One missed oppurtunity here was for them to have an osmotic control: you see, a lot of the antibacterial properties of preserves like honey's and jam come through the fact that they mess with the osmotic balance of bacteria like Streptococcus pyogenes and cause them die out. Having a control with a compound that exerts the same osmotic pressure would give the researchers an opportunity to more finely tease out the antibacterial activity of manuka honey. If the manuka honey exerts a greater inhibitory effect than this control, then you can move on and try out some of the compounds said to give manuka honey it's effect, such as methylglyoxal. If you really had time to spare, you could test out each constituent, to see which is exerting the inhibitory effect, or even more interesting, whether one or more components are necessary in order to do this. But i'm letting my imagination run wild here, on to the next figure.


Figure 2
The next step was for them to look at the aggregation of the bacteria. They did this by using an interesting technique. They grew up the bacteria in C-media. This media basically forces S. pyogenes to form biofilms. Anyway, they let these bacteria grow overnight, and then they centrifuged them, so that all the bacteria would clump together in a nice pellet, which will allow the bacteria to be separated from their liquid culture.
The researchers then added Todd Hewitt media (which is S. pyogenes favourite media to grow in) mixed with manuka honey at 5% and 10% w/v.  They mixed all the bacteria together, and put it into an optical cuvette.
Remember what i told you earlier about bacteria absorbing light? that applies here. The mixture they have is now full of bacteria, and they can now measure the reduction in the numbers of bacteria in the same way. The more light that goes through, the less bacteria present.

This method is based off of a platelet aggregation assay used in this study from Howard Jenkinson's group, where they took a bunch of platelets, and added a relatively small amount of S. pyogenes. Since S. pyogenes  binds to platelets, the addition of strep caused all of the platelets to stick to the bacteria, and precipitate out of culture. In that study, they specifically looked at the reduction of light transmission through platelets which has S. pyogenes added, and compared that to a culture with no S. pyogenes added. So they switched this technique around, and used it to measure the level of aggregation of the bacteria. Bacteria which had no manuka honey added naturally aggregated and fell out of solution, leading to a decrease in optical density. Those which did have manuka honey in them stayed in their planktonic state. The main reason I like what they did here was that they had this technique from another paper, and realised that it could be useful for their research if they changed it in the right way. I would have liked for them to display their aggregation data as a time course, so you can see the actual differences in optical density develop as the bacteria aggregate out of culture. I can't really think of any reason why they couldn't show that data, but nevermind. You can't have everything.


Figure 3

Here is where they directly monitored biofilm formation through a crystal violet staining method. Crystal Violet is a cool little chemical that is deep purple, and binds to bacterial cell walls. So if you have some bacteria on a plate, and add crystal violet to them, they will become purple. So how does this property allow for biofilms to be measured ?
Well, if you grow S. pyogenes in a well, it will form biofilms at the bottom. These biofilms allow the bacteria to stick to the surface of these wells. So in any one culture, you'll have some bacteria floating around, minding their own business, and some stuck to the side in biofilms. It is these stuck down bacteria that we want to quantify.
So they washed out the plates with phosphate buffered saline, so that the only bacteria left in these wells were the ones stuck to the sides. But how do you assess the numbers of bacteria present in these wells ?
that is where our fried crystal violet comes in. You add crystal violet to the bacteria, and let it bind to their cell walls.Then wash off any excess crystal violet, so that the only crystal violet left is attached to the cell walls of the bacteria. They then used acetic acid to get the crystal violet out of the remaining cells. The amount of crystal violet is proportional to the amount of bacterial cell wall present. By looking at how it absorbs light, you can get an idea of how much biofilm has been formed in each well.
Have you spotted the problem with this technique yet ?
 Crystal violet staining only quantifies the cells which are bound to the well. So if there is a change in total bacterial numbers (which is what we'd expect based on the Figures), then that will show up as a decrease in biofilm formation. One way around this would be to collect the cells from the supernatant and applying the same technique to them. I went as far as creating a standard curve to show that crystal violet optical density is directly proportional to viable bacterial numbers. So while this data is promising, without an idea of the total bacteria present in the wells, it isn't very useful.



Figure 4
So what do these colonies look like under a microscope if they've been grown with manuka honey as opposed to nutrient media alone ? Well, if you grow them on a cover slip, wash them in PBS and add crystal violet and look at them under a microscope, you can try to look for differences there. And it is true that there are microcolonies on one slide and a few loose bacteria on the other. So I would agree that based on this image, Manuka honey does prevent microcolony formation.


Figure 5
A) I liked this figure, as it showed the correlation between the biomass of the bacteria in the biofilms compared with an estimation of the bacterial numbers within the biofilm. It shows that the more manuka honey you add to a solution, the less bacteria are present within the biofilm.
B) This figure is interesting, as it shows how quickly the manuka honey acts to kill off the bacteria, with the addition of 40% acting almost instantaneously to turn happy gree bacteria into unhappy red bacteria.
C) This is where I finally have my main criticism addressed ! They grew up bacteria in biofilms with different concentrations of manuka honey, and every 30 minutes for two hours to see if there was a difference in the numbers of bacteria in a planktonic state.  And to be fair, there does seem to be an increase in the numbers of S. pyogenes present in the planktonic state at 10% and 20%, which does strongly indicate that bacteria are being released from biofilms, and are being killed at 40%.
 However, at no point do they compare the numbers of bacteria released from the biofilms to the numbers present, again. In fact, it seems the thing that irritated me in the crystal violet assays has been reversed. There, I was annoyed at the measurement of the biomass of the biofilms alone, and here only the numbers of bacteria in the suspension were being measured.
So someone with a far greater supply of cynicism than I do could explain these results as being caused by a spike in bacterial growth caused by the addition of the honey. Without both sets of data, slapping down critics is very difficult.  However, this was still the missing piece that I was looking for in the previous data, and I am willing to give the authors the benefit of the doubt. Onto the next figure !



Figure 6
Streptococcus pyogenes causes necrotizing fasciitis (also known as the flesh eating disease). Usually it comes out of nowhere, and starts attacking a part of the body, seemingly at random. One consistent thing seen in many cases that it's victims often suffer some sort of trauma before the onset of the disease. A bruise can suddenly become the target for Streptococcus to attack. One of the theories is that when the body gets wounded, certain proteins are more greatly expressed in the areas where there are wounds. Streptococcus pyogenes is known to bind to these proteins.
So the basic premise of the experiment in figure 6 is to see whether Manuka honey prevents S. pyogenes binding to these factors, by interfering with the way that S. pyogenes itself works. So how did this group look at this?
They  took fibronectin and fibrinogen proteins and bound them to the surfaces of a well. So they added bacteria to the wells, and let them bind to fibrinogen or fibronectin. They then let the biofilms grow, and used a crystal violet staining assay to assess the bacteria present within the biofilm. At least, that's what they say in their methods. You see, if you cast your eye to the Y-axis of that particular figure, you will see that there are bacterial numbers rather than optical density. Puzzled ? I was.
This is not to say that there is not a viable way of extrapolating bacterial numbers from a crystal violet staining assay. as I explained earlier, it is not actually very difficult. It can be as easy as taking a concentrated sample of bacteria, performing serial dilutions, and take one sample to assess colony numbers, and  centrifuging the rest down into a pellet and then doing the crystal violet staining bioassay. Then you can create a standard curve which you can use to extrapolate bacterial numbers. Of course , I appreciate that these researchers may have been bold enough as to present this without also presenting the standard curve, or even mentioning it in the methods.
Anyway, they find that fibronectin binding is significantly reduced in the presence of the honey. again, we don't know whether the proportion of the bacteria binding to the wells has changed rather than there being more or less bacteria present. S. pyogenes just seems to bind fibronectin a lot more avidly than the other substrates (PBS, no ligand and fibrinogen).



Figure 7
Thankfully, the experiment presented here is one of the higher points of this paper, and goes further for supporting the title of their paper than the last one did. Serum opacity factor (sof) and Streptococcal fibronectin binding-protein 1 (sfb1) would be the proteins involved in binding fibronectin. So how did they go about measuring their expression? They used a method to look at the numbers of RNA transcripts within each cell. They convert these RNA transcripts into cDNA. Polymerase chain reaction is then used to amplify the numbers of cDNA transcripts, by adding some nucleic acids and a DNA polymerase.
 They then ran these on a gel and imaged them. The size of each band is meant to correlate to the amount of RNA transcript present. They then measured the brightness of each band using densitometry. They used a house keeping gene (a gene that is expressed all the time) to compare the expression of the sof and sfb1.
Their results from this definitely seem to suggest that sof is reduced in the presence of honey compared to without. Unfortunately, they only show one gel image, which essentially just one replicate in their data. The densitometry values for all of the bands are what I want to see, so I know that the standard deviations for each band are small, rather than having to assume it.  And if I really wanted to be cynical , I could point out that there may be a lot of the housekeeping gene present already, and that if there is enough then even if there are small numbers of bacteria present, there is enough for the reaction to reach saturation, and thus no difference would be seen in the controls. One way to shut down that criticism would be to try another method of RT-PCR which takes measurements throughout the PCR reaction, so that it is absolutely clear whether such a thing is happening. Or even select a number of house keeping genes, and work out which one would be the best for this task. But for me, that doesn't matter, because I really want to believe in this paper.
Since there are no more figures, I guess I have to summarise my thoughts on this paper.

Summary


  They show that manuka honey does kill off S. pyogenes, that much alone is certain. They also provide some evidence that it disperses biofilms. My main criticisms of this paper focus on the fact that in many experiments, they at no point measure the proportion of bacteria within a biofilm compared to the total bacteria present within a culture, so in any one experiment it is very difficult to tell whether there is actually an effect on biofilm, or whether it is an artefact of the growth of the bacteria.
But does this actually compromise the findings of the paper? I still think that their assay for looking at S. pyogenes aggregation was pretty good. Also, looking at the paper as a whole, it does provide some evidence that honey disrupts biofilms, simply because that is the best explanation for all of their data. It is not comprehensive, but I'm willing to give them the benefit of the doubt.
Wound infection with S. pyogenes are a terrible problem, and the reason why a lot of research into S. pyogenes in the past was performed by the military. When a wound gets infected, streptococci sit in biofilms on the surface of the wound. Of course, the patient doesn't notice it's presence until the biofilms become big enough to induce a reaction from the immune system, and that is when they usually get their course of antibiotics. And that's only in the lucky situation that they get to a doctor before the S. pyogenes breaks free of its biofilms and invade the circulatory system, causing a disease known as Streptococcal Toxic Shock Syndrome, which is a far more severe disease. But if this paper is to be believed (and I think there is enough convincing evidence here to prove it) manuka honey forces S. pyogenes to break free of it's biofilms long before it experiences any toxic effects. Can you see where there may be an issue here ? A treatment that acts to preferentially releases bacteria into your circulation over killing them is not something you'd give to someone you particularly like.
That is why I'm willing to give this paper the soft treatment. Because even if we ignore the methodological flaws, the absence of novelty, we are still left with a paper with data that despite anything should warn clinicians away from the use of manuka honey in practice. Ultimately, what felt so wrong about this paper is the lack of curiosity of how manuka honey actually works. If they wanted to look at that, they would have looked at each individual component of it. What they focused on was breaking down biofilms, because of the assumption that biofilms are bad, and thus breaking them up is always good. But it's not that simple, especially when it comes to wound colonisation. Yes you could argue it's preventative, but you need to have a concentration of 40% honey to actually kill the bacteria, and is that really better than ethanol, or other disinfectants?
So if you're tired of your boring old wound infection, and want a nearly fatal case of streptococcal toxic shock syndrome, just add manuka honey.

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