Dear Abhishek,

for most simple metabolites, the loss in their pools due to biomass growth is small compared to their total rate of production. Typically, it is important to consider removal of biomass precursors for protein (amino acids), RNA/DNA (nucleotides), lipids (mainly acetyl-CoA moieties, but without the CoA), and sugar polymers (e.g. glycogen) are important to consider. This data can be inferred from observed uptake rates (e.g. of glucose, ammonium) and the growth rate quite well when you have a known biomass composition. If you really want to account for loss due to cell growth, the dilution term mu*c_intra (mu: specific growth rate, e.g. in 1/h, c_intra: intracellular concentration, e.g. in mmol/L_cellvol) must be computed. As you see, c_intra requires absolute concentration values. So if you have samples with a standard addition for your metabolites of interest for at least one of the samples, you may calculate these terms. Just relative intensities like form an MS are insufficient, because different metabolites at the same concentration tend to give quite different signal intensities. You can compare signals for the same metabolite between different samples, but not intensities between chemically different metabolites.

Dear Dirk,

Thank you for the answer. I have a related doubt. Let's say I have a time series metabolomics data where the intensities of metabolites are reported for the log phase.  I take an average for the different time points and I get an average intensity for each metabolite. Just by looking at the average intensities of each metabolite one can compare the probable expression or quantitative presence of that metabolite over the time series. Can I sum these average intensities and calculate the fraction of metabolites that are part of the sum? By relative intensities, I tried to mention this value. The reason for summing up the average intensities is to get a sum total average intensity that would represent the total metabolite pool in the cellular environment. The fractional (relative) intensities would talk about probable fraction of metabolite from the total pool. This in turn will mean the available fraction of each metabolite to contribute for the biomass. Maybe one can think of normalizing intensities by the molecular weight of the metabolite. Does this logically sound correct?

Dear Abhishek,

I thought you might have something like this in mind. True, if you had an idea of the total pool of free metabolites in a cell (there is some literature on that), you could suspect that by summing over relative intensities of all metabolites at a given time point you could get an estimate of their relative concentrations at that time point and even convert that to an absolute value using the total metabolite concentration estimate.

However, for this you implicitly assume that, say, 1mM of ATP in your sample gives you the same relative intensity than 1mM of pyruvate. Unfortunately, this is not true in most metabolomics measurement methods (e,g, LC-MS, GC-MS) as signal intensity varies significantly with chemical nature of the metabolite (not to speak of matrix effects).

But if you could get an idea of the intensity to concentration relations of the most predominant metabolites in your sample, you can maybe get an approximate estimate of the relative content of the remaining metabolites.