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closeCompliment & Queries
Posted by jfierer on 26 Apr 2008 at 23:23 GMT
1. I think this is a great approach to mapping QTL for resistance to infection and the work was done with care. Congratulations. I would like to know what the method was that you used for normalizing the results from one experiment to the next. You mention multivariate analysis but do not say what the variables were and how that was translated into a quantifiable phenotype.
2. How do your expression results relate to your gene mapping?
3. Can you be sure that the differences in gene expression were not the result of rather than the cause of the difference in susceptibility? When we looked at TNF expression by mice that are susceptible or resistant to Salmonella there was no difference if we adjusted the inoculum so that they both had similar numbers of bacteria, whereas there was a huge difference if we did not.
RE: Compliment & Queries
nourtan replied to jfierer on 21 May 2008 at 09:10 GMT
Thank you very much for your comprehensive review of our paper.
Regarding your first question,
"1. I think this is a great approach to mapping QTL for resistance to infection and the work was done with care. Congratulations. I would like to know what the method was that you used for normalizing the results from one experiment to the next. You mention multivariate analysis but do not say what the variables were and how that was translated into a quantifiable phenotype."
Normalizing the results from one experiment to the next was one of our main concerns in our design. We used general linear model (GLM) OLS ANOVA correcting for age, sex, and body weight as covariates. We measured three main phenotypes, survival, bacteremia, and bacterial load in tissues.
For survival, measured as survival days post-injection, we normalized across experiments by inspecting survival days distribution clusters for each experiment separately. We determined multimodal distribution in each experiment and boundaries of each cluster for a total of three clusters: susceptible, intermediate, and resistant. We then converted survival days within each cluster into a survival index ranging from 0.25–1, 1.25–2, and 2.25–3 for susceptible, intermediate, and resistant clusters respectively and assigned survival index to each mouse irrespective of its strain. We then corrected indices for each strain, across experiments for significant covariates, age, sex, and body weight, using GLM analyses.
We measured bacteremia 24 h post-injection, expressed as log CFU/ml, and similarly corrected for sex, age and body weight. Similarly, we corrected bacterial load in spleens, which we quantified as log CFU/organ.
In summary, we performed three sets of analyses for the following three phenotypes: (1) corrected relative survival index, (2) log bacterial load in blood 24 h post injection, and (3) log bacterial load in spleen at expiration.
"2. How do your expression results relate to your gene mapping?"
This is a very interesting question; we are currently investigating this very point in greater detail. Our preliminary data suggest that the observed differences in gene expression of the tested genes reflect their direct role in defining susceptibility to infection. Also, several of the differentially expressed genes show polymorphisms as single nucleotide polymorphism (SNPs) between the parental strains B6 and D2, suggesting that these polymorphic genes modulate differential response to infection. The differentially expressed genes we show in the manuscript are located on mapped QTLs on Chr 2. In addition, we are conducting genome-wide expression analyses and initial results concur with our gene mapping analyses.
"3. Can you be sure that the differences in gene expression were not the result of rather than the cause of the difference in susceptibility? When we looked at TNF expression by mice that are susceptible or resistant to Salmonella there was no difference if we adjusted the inoculum so that they both had similar numbers of bacteria, whereas there was a huge difference if we did not."
This question is the core of our studies, and we hope we could further address it in our future studies; currently we are confident that the differentially expressed genes are the cause rather than the effect of difference in susceptibility. Our confidence stems from our approach, which was to determine causes of differential susceptibility to GAS sepsis in a genetically diverse population.
The second part of your question regarding inocula, we have used the same inoculum for infecting both susceptible and resistant strains.
RE: Compliment & Queries
ramy replied to jfierer on 28 Apr 2009 at 09:09 GMT
Dear Joshua,
A more comprehensive response to your question #1 (concerning the statistical basis for the normalization methods) is detailed in our first paper describing this model
Genes Immun. 2007 Jul;8(5):404-15. Epub 2007 May 24.
Susceptibility to severe Streptococcal sepsis: use of a large set of isogenic mouse lines to study genetic and environmental factors. (PMID: 17525705).
http://www.nature.com/gen...
Unfortunately, the linked URL allows readers to only access the abstract, while the full text requires subscription. But I assume that this paper will be fully released soon as the study was partly funded by the NIH.
Ramy K. Aziz
Department of Microbiology and Immunology, Faculty of Pharmacy, Cairo University, Cairo, Egypt