The stream of new technological advancements and their integration into the field of microbiology have contributed significantly towards our understanding of life in the micro-scale world, making the fields of microbiology and biotechnology shine like never before. Since 1980, the recombinant protein-based therapeutics industry has become one of the fastest growing sectors in the biopharmaceutical market. Nearly 30% of commercially available recombinant proteins are produced in Escherichia coli, making this species one of the most commonly used bacterial expression systems for the production of recombinant biotherapeutics. However, when it comes to the production of enzymes and bioactive secondary metabolites (antibiotic, antifungal, antiviral and immunosuppressant), Streptomyces species remain the major producer within this sector. Meeting the high demand for such products requires a clear and in-depth understanding of the bioprocesses involved to achieve high yield and quality products, whilst keeping the process industrially attractive. It is generally accepted that the metabolome, as a down-stream process to the genome and proteome, may provide a clearer picture of a biological system. Thus, in this thesis a series of metabolomics approaches were adopted to obtain a deeper insight into the metabolic effects of recombinant protein production in E. coli and Streptomyces lividans. Furthermore, a Geobacter-based biomagnetite nanoparticle production system which displayed a prolonged lag phase upon scale-up was investigated by employing metabolic profiling and fingerprinting approaches combined with multivariate analysis strategies, to identify growth-limiting metabolites. The results of this analysis identified nicotinamide as the growth limiting metabolite. Nicotinamide-feeding experiments confirmed the above findings, leading to improved biomass yield whilst restoring the lag phase to bench-scale level. Raman and Fourier transform infrared spectroscopies combined with stable isotopic probing strategies were also employed to demonstrate the application of metabolic fingerprinting in providing detailed biochemical information for quantitative characterisation and differentiation of E. coli cells at community and single-cell levels. The single-cell approach proved promising, offering detailed biochemical information and perhaps accompanying other cultivation-free approaches such as metagenomics for further future investigations. It is hoped that the advances made in these studies have proved the potential applications of metabolomics strategies to aid the optimisation of microbially-driven bioprocesses.