For decades, researchers have lacked the ability to rapidly correlate microbial identity with bacterial metabolism. Since specialized metabolites are critical to bacterial function and survival in the environment, we designed a data acquisition and bioinformatics technique (IDBac) that utilizes in situ matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze protein and specialized metabolite spectra of single bacterial colonies from agar plates. We demonstrated the power of our approach by discriminating between two Bacillus subtilis colonies in under 30 minutes, which differ by a single genomic mutation, solely on the basis of their differential ability to produce cyclic peptide antibiotics surfactin and plipastatin. Next, we employed our IDBac technique to detect subtle intra-species differences in the production of metal scavenging acyl-desferrioxamines in a group of eight freshwater Micromonospora isolates that share >99% sequence similarity in the 16S rRNA gene. Finally, we employed our method to simultaneously extract protein and specialized metabolite MS profiles from unidentified species of Lake Michigan sponge-associated bacteria cultivated on an agar plate. In just 3 hours, we created hierarchical protein MS groupings of 11 environmental isolates (10 MS replicates each, for a total of 110 samples) that accurately mirrored phylogenetic groupings. We further distinguished isolates within these groupings, which share nearly identical 16S rRNA gene sequence identity, based on inter- and intra-species differences in specialized metabolite production. To our knowledge, IDBac is the first attempt to couple in situ MS analyses of protein content and specialized metabolite production to allow the distinction of closely related bacterial colonies.SignificanceMass spectrometry is a powerful technique that has been used to identify bacteria via protein content, and to assess bacterial function in an environment via analysis of specialized metabolites. However, until now these analyses have operated independently, and this has resulted in the inability to rapidly connect bacterial phylogenetic identity with patterns of specialized metabolism. To bridge this gap, we designed a MALDI-TOF mass spectrometry data acquisition and bioinformatics pipeline (IDBac) to discriminate both intact protein and specialized metabolite spectra directly from bacterial cells grown on agar. To our knowledge, this is the first technique that organizes bacteria into highly similar phylogenetic groups and allows for comparison of metabolic differences of hundreds of isolates in just a few hours.