is a leading contributor to infectious diarrhea and child mortality worldwide but it remains unknown how alterations in the gut microbiome vary for distinct pathotypes and whether these signatures can be used for diagnostic purposes. Further, the majority of enteric diarrheal infections are not diagnosed with respect to their etiological agent(s) due to technical challenges. Towards addressing these issues, we devised a novel approach that combined traditional, isolate-based and molecular biology techniques with metagenomics analysis of stool samples and epidemiological data. Application of this pipeline to children enrolled in a case-control study of diarrhea in Ecuador showed that, in about half of the cases where an pathotype was detected by culture and PCR, was likely not the causative agent based on metagenomic-derived low relative abundance, level of clonality and/or virulence gene content. Our results also showed that diffuse adherent (DAEC), a pathotype that is generally underrepresented in previous studies of diarrhea and thus, thought to not be highly virulent, caused several small-scale diarrheal outbreaks across a rural to urban gradient in Ecuador. DAEC infections were uniquely accompanied by co-elution of high amounts of human DNA and conferred significant shifts in the gut microbiome composition relative to controls or infections caused by other pathotypes. Our study shows that diarrheal infections can be efficiently diagnosed for their etiological agent and categorized based on their effects on the gut microbiome using metagenomic tools, which opens new possibilities for diagnostics and treatment. infectious diarrhea is an important contributor to child mortality worldwide. However, diagnosing and thus, treating infections remains challenging due to technical and other reasons associated with the limitations of the traditional culture-based techniques and the requirement to apply Koch's postulates. In this study, we integrated traditional microbiology techniques with metagenomics and epidemiology data in order to identify cases of diarrhea where was most likely the causative disease agent and evaluate specific signatures in the disease-state gut microbiome that distinguish between DAEC, ETEC and EPEC pathotypes. Therefore, our methodology and results should be highly relevant for diagnosing and treating diarrheal infections, and have important applications in public health.