During evolution, each bacterial strain shapes its metabolism in order to colonise a diversity of niches. Unraveling the biochemical reactions underlying bacteria metabolism is important for biotechnological purposes and for understanding relationships within a complex microbiome as well as the microbiome’s connection with its host. Here we propose a new approach to identifying active metabolic pathways, by integrating essentiality analysis and protein abundance. As an example, we used two bacterial species (Mycoplasma pneumoniae and Mycoplasma agalactiae) that share a high gene similarity yet show significant metabolic differences. After integrating all available metabolic knowledge about their enzymes, metabolites and reactions, we built detailed metabolic maps of their carbon metabolism. We determined the carbon sources that allow growth in M. agalactiae (as known for M. pneumoniae) and introduced glucose-dependent growth in M. agalactiae. By analyzing gene essentiality and performing quantitative proteomics, we could predict the active metabolic pathways and directionalities for the sugar, phospholipids, DNA/RNA precursors, glycoproteins, and glycolipids metabolism of these two bacteria. Comparison between predicted and experimentally determined active pathways shows an excellent agreement. Thus, protein essentiality profiling using transposon sequencing analysis combined with quantitative proteomics and metabolic maps could be used to determine and engineer metabolic fluxes.