Update information. The value of synthetic microbial communities in biotechnology is gaining traction due to their ability to undertake more complex metabolic tasks than monocultures. However, a thorough understanding of strain interactions, productivity and stability is often required to optimize growth and scale up cultivation. Quantitative proteomics can provide valuable insights into how microbial strains adapt to changing conditions in biomanufacturing or bioremediation scenarios. However, current workflows and methodologies are not suitable for simple artificial co-culture systems where strain ratios are dynamic. Here, we established a standard workflow for co-culture proteomics using an exemplar system containing two key members, Azotobacter vinelandii and Synechococcus elongatus. Factors affecting the quantitative accuracy of co-culture proteomics were investigated, including peptide physicochemical characteristics such as molecular weight, isoelectric point, hydrophobicity, and dynamic range, as well as factors relating to protein identification such as varying proteome size and shared peptides between species. Different quantification methods based on spectral counts and intensity were evaluated, demonstrating good correlations between protein amount and the six quantification methods at the protein level. We propose a new normalization method, named “LFQRatio”, to reflect the relative contributions of the two distinct cell types emerging from the cell ratio changes during co-cultivation. LFQRatio can be applied to real co-culture proteomics experiments, providing accurate insights into quantitative proteome changes in each strain.