Normally the TSP solution is the one so that the total cost on edges is minimal.
However in my case I need a specific edge on the solution, it does not matter if it the solution is not optimal anymore.
It does matter, however, that of all Hamiltonian cycles containing that edge the obtained solution is optimal. Or at least bounded.
More formally the problem would be: given a complete metric graph and a specific edge, what is the Hamiltonian cycle which cost is minimal passing through that specific edge?
Edit: transform the graph is probably a good idea. But keep in mind the resulting graph must still be metric and complete. A non-complete graph is equivalent to a non-metric one in this case, just think that the missing edge is actually an overly expensive one. This is important because there cannot be polinomial-time algorithm for general distances. If you are curious the proof of this fact is in "P-complete approximation problems" of S. Sahni and T. Gonzalez (1976).