We compared the gas chromatography-mass spectrometry (GC-MS) metabolite profiles of mouse tumour necrosis factor alpha (mTNF-alpha) secreting Streptomyces lividans TK24 to the non-secreting wild type and the wild type harbouring the empty pIJ486 plasmid by multi-block principal component analysis (PCA). The multi-block PCA model successfully identified peaks that were statistically different between the protein secreting and non-secreting strains, and at the same time also uncovered the efficiency of intracellular metabolite extraction by an ultrasonic adaptive focused acoustics (AFA) technique compared to a manual vortex/freeze-thaw method. Fifty-one metabolites were significantly different between the three biological strains and 17 of these were abundant in the mTNF-alpha secreting strain compared to the non-secreting strains. No significant differences in the number of detected metabolite peaks were observed between the two extraction techniques. However, from the loadings of the multi-block PCA model, as well as univariate statistical analysis, we observed that the relative peak response ratios to the internal standard of 10 metabolites were higher for the AFA extraction, suggesting a more efficient recovery of these metabolites than achieved with the manual vortex/freeze thaw method.