An accurate identification and characterization of pathogens is crucial in disease management. The appropriateness and
effectiveness of the microbial diagnosis method influence the choice of the antimicrobial agent to be used in the treatment
of infection. Traditionally, bacterial diagnosis is based on conventional and culturing-dependent approaches, such as
culture and counting methods, generally coupled to morphological and physiological characterization. Currently, rapid
technological advances in bacterial identification methods are occurring providing a bewildering wide range of techniques
to detect, identify and differentiate bacteria. Molecular methods, such as ELISA and PCR, had introduced great
improvements in bacterial identification as they contributed to speed up the analysis and the reduction of handling.
However, it has been demonstrated that heterogeneous microbial communities are the main cause of several human
infections. This genetic and phenotypic heterogeneity is crucial to microorganisms achieving adaptation to human host,
and it might reflect distinct pathogenicity potential. The aforementioned molecular methods and new emergent methods,
such as MALDI-TOF MS, have still limitations in full identification and differentiation of microbial heterogeneity.
Therefore, a new generation of diagnosis methods able to detect and characterize microbial heterogeneity should be
developed. Microbial infections are like dynamic systems and it is essential that diagnosis methods and technologies
rapidly evolve to detect and measure changes occurring at individual and population level. This new kind of methods will
allow a relevant shift about infection development understanding, as well about microbial mechanisms of resistance to
antibiotics and human defences and persistence ability in human host that culminate in better medical decisions about
antimicrobial therapy
