In my research I use atomic force microscopy (AFM) to study bacterial cell adhesion properties. I optimized the parameters in force ramp menu, but sometime the force curve show no adhesion events or very weak. When I’m preparing a histogram (distribution of adhesion force) should I ignore the force curve with no adhesion or include them? Maybe I must show it on histogram but don’t take them to calculate the mean value?
I measured the rupture length and adhesion force. The adhesion force was determined by the peak with the maximal adhesion force, and the rupture length was defined by the length from the contact point to the rupture point of the last adhesion peak. I want to know if I’m doing it correctly (see Fig. 1).
How to determine on force curve the pull-off distance and pull-off force? Could you please draw this parameters on my force curve (Fig. 2).
Hallo,
in my opinion, because you are trying to understand the bacterial response to the different compounds, you need to take into consideration the whole data for the hystogram, then you should make some negative and positive control tests and compare the data:e.g. using some compound that brings to zero the adhesion, or using a blocking compound, that is something that make the first compound be non-active. Then when you'll have different experimental data you need to compare the statistics of them. About the pull-off distance and force, I am not sure of what you mean.... Maybe the best parameter would be to consider the retract area underneath the retract part of the curve, which shows you the work done (J). Interesting new results could be obtained performing experiments at different loading rates and with different substrates. In addition, how are you performing the experiment? do you use a bead? or do you pick-up the bacterial cell to the probe?
good luck!
the question is what you need to answer: I mean if you are studying a population you need to put also the negative data in the histogram and mean. But you can also choose to show the histogram with whole data and the mean value for the positive data, but saying it.
Pull-off is a very general term, you will need to try to understand better what do they refer to...
Moreover as far as I understood you are making a selection of cell population, before making the real measurements. When you say "best samples" do you mean the ones that show adhesion? If yes, later you can only infer a partial result on the single cell you are studying, but maybe you don't have interest in the whole population... As per your first question related to Fig. 1, you are doing it correctly.
I agree that adhesion properties are not only important for mammalian cell-cell interactions, but also bacterial entry into organisms. You seem to study different bacterial strains and want to compare their adhesion properties. From what I could understand from your latest conference abstract you measure bacteria on gelatin against an unmodified cantilever (???). Please correct me, if I am wrong! Or, did you functionalize the cantilever with any biological molecules? Otherwise you measure bacteria - surface of a cantilever interactions, but why? Of course, adhesion of bacteria to any surface may be important in many ways, it is just not clear to my why you want to compare two bacterial strains to the surface of a cantilever. (I recently critisized a very strange publication by others who thought they were measuring cancer cell adhesion, but have covalently bound the cell to a cantilever, which did not reflect any physiologic cell adhesion, see my published comment below).
So, maybe you will compare bacterial adhesion to cantilever tips, which have been functionalized with some specific or unspecific protein (might be just more physiologic than a normal tip), then you should of course mention the frequencies of adhesion vs. no adhesion. But for characterizing the adhesion events, I suggest you focus on the mean of adhesions, i.e. not including the non-adhesive events. It could be a different time scale of the adhesion to be formed: some bacterial strain may need much more time to adhere than the other, but the individual adhesion molecules might bind better... Some investigators like the idea of comparing the "integrated area" under the curve and may describe this as "work force", or similar. This may help you if you see differences between the bacterial strains or conditions you want to characterize.
Article Comment on “A method to measure cellular adhesion utilizing ...
Although it focuses more on cell adhesion of mammalian (incl. human) cells and at the (so-called) single-molecule level, I would like to point to my recent book chapter. To the best of my knowledge today I was the first in the world to establish "specificity" of AFM measurements between two living mammalian cells (Eibl et al., 2004). Unfortunately, my life's work then was sabotaged and overtaken. I also published some step-by-step protocols (e.g. Eibl and Moy) for use of measuring mammalian cell adhesion with AFM under physiologic conditions. My major invention was to measure for the first time, the physiologic activation of any integrin by any chemokine on any (mammalian) cell type.
Chapter Single-Molecule Studies of Integrins by AFM-Based Force Spec...
Thank you very much for all your suggestions.
I study the effects of different compounds on bacterial ability for adhesion.
In the first step of my research I want to determine their effect on bacterial adhesion by registering force curves between the unmodified AFM tip and the bacterial cell surfaces. Then for the the most efficient compound I will make a single-cell bacterial probes.
Thank you for clarifying and confirming my understanding. I think it will be critical to tell the future reviewer what exactly you wanted to measure; I am sceptical to call this "adhesion", since bacteria usually never need to adhere to a cantilever. Perhaps, you want to find some anti-adhesive/repellent compounds to protect surfaces from bacteria, then I would suggest to modify the cantilever to achieve first good or typical adhesion. For studying more physiologic adhesive events, perhaps, coating with some natural proteins or sugar compounds might be best (BSA, biotin+streptavidin+ConA; or Poly-D-Lysine). Such an approach would allow differently charged areas of natural substances and might increase the basal adhesion (frequency and force), and therefore allow shorter contact times, but most importantly, may allow better interpretation and detection of the data - and identifying even small contributions to an adhesive change.
Thank you very much for your very valuable input.
I will definitely take all these suggestions into consideration.
- Badges
- Science topic
- Similar topics
- Biological Science
- Biochemistry
- Biomolecules
- Peptides