FIR Filter design by non-equal samples I'd like to design a Digital Differentiator with a pre-specified lowpass characteristic.

I've tried Wiener Filters (using inverseFFT to transform from frequency to time-domain), Savitzky Golay and others. Intuitively, I've come to the conclusion, that by specifying DFT points, i.e. uniformly distributed samples of the frequency response, one can achieve only a maximal low-pass frequency. For example using $N$ points, the minimal lowpass frequency would be $1/N$ bins of the FFT, thus $\pi/N$ $rad/sample$.

Is this notion correct?

And further along this path: if it's true, is this a universal boundary, or are there methods, where one can implicitly or explicitly specify not-equally sampled frequency points and thus achieve lower stopband frequencies with FIR filters?

For IIR filters I think this is no problem, since with a simple $1/(z+a)$ one can choose $a$ to achieve a variable stopband frequency just as in the continuous case.
The Remez exchange method isn't limited to DFT bin constraints so to answer your question, no FIR filters do not have the limitation you hypothesized.    

If you can find METEOR, a program written in part by Tom Parks, you can be fairly free in your filter specifications provided they are feesable

and there is 

http://gmeteor.sourceforge.net/