Analysis of the metaproteome of microbial communities is important to provide an insight of community physiology and pathogenicity. This study evaluated the metaproteome of endodontic infections associated with acute apical abscesses and asymptomatic apical periodontitis lesions. Proteins persisting or expressed after root canal treatment were also evaluated. Finally, human proteins associated with these infections were identified. Samples were taken from root canals of teeth with asymptomatic apical periodontitis before and after chemomechanical treatment using either NaOCl or chlorhexidine as the irrigant. Samples from abscesses were taken by aspiration of the purulent exudate. Clinical samples were processed for analysis of the exoproteome by using two complementary mass spectrometry platforms: nanoflow liquid chromatography coupled with linear ion trap quadrupole Velos Orbitrap and liquid chromatography-quadrupole time-of-flight. A total of 308 proteins of microbial origin were identified. The number of proteins in abscesses was higher than in asymptomatic cases. In canals irrigated with chlorhexidine, the number of identified proteins decreased substantially, while in the NaOCl group the number of proteins increased. The large majority of microbial proteins found in endodontic samples were related to metabolic and housekeeping processes, including protein synthesis, energy metabolism and DNA processes. Moreover, several other proteins related to pathogenicity and resistance/survival were found, including proteins involved with adhesion, biofilm formation and antibiotic resistance, stress proteins, exotoxins, invasins, proteases and endopeptidases (mostly in abscesses), and an archaeal protein linked to methane production. The majority of human proteins detected were related to cellular processes and metabolism, as well as immune defense. Interrogation of the metaproteome of endodontic microbial communities provides information on the physiology and pathogenicity of the community at the time of sampling. There is a growing need for expanded and more curated protein databases that permit more accurate identifications of proteins in metaproteomic studies.