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PCR detectable units - PDU (Feb/12/2007 )

hello all,
i would like to now if any one out here has done a PCR detectable unit assay for a given sample, this method is usually followed to find the least detectable number in the sample, eg. virus or bacteria. i would like to know the protocol for this if anyone has done it, and also if the virus is a rna then a cdna is usually used to calculate the PCR detectable units, so is there a procedure change in that method.

the kid


Just use aknown target (eg a plasmid with your target) with a known concentration. Calculate the copy number
1 mole(in grams) = Avagados constant = 6 X 10e23 molecules
If you know the size of the gene (bp) the mol wt of a nucleotide (or pair for DNA), and concentration of the plasmid ug/ul, the it is a simple matter of calculating out the number of moles and hence the copy number.

Make dilutions to establish what your sensitivity is for your assay. In general it is better to use qPCR for this type of assay.
For RNA you can use an in vitro transcribed target and calculate the copy number. Again, just make serial dilutions.


thank you for the reply, but i have a query, i read in a paper something different about estimating the initial concentration of the RNA, i am pasting a part of the paper please tell me if this is possible and if so, any reference for the method would be nice.

The numbers of virus particles present in water were
estimated by culture or by RT-PCR on 10-fold serially diluted RNA (end point
dilution). Virus concentrations in the undiluted samples were estimated as most
probable numbers by the use of the number of PFU or the presence or absence
of virus genomes in the 10-fold RNA dilutions, under the assumption that
negative samples do not contain virus or viral RNA. Application of the Poisson
distribution was justified by the assumption that the infectious virus particles or
viral RNA was dispersed randomly in the sample. The maximum likelihood
method was used to estimate the number of virus particles in the undiluted
sample. A negative binomial model gave the best fit for the distribution of
virus particles in the original and diluted samples. The 95% confidence interval
was estimated for each virus concentration.

as you see they have used negative binomial model to give best fit for the undiluted sample to find the initial concentraiton of the virus. i did not get this part.