microbial identification, such as analyzing direct positive blood cultures for identification of pathogens, sub- species and strain typing, detection of drug resistance determinants, and generating specialized metabolite MS profiles to assess bacterial functional traits (Florio et al.; Clark et al., 2018; Oviaño and Bou, 2018). Most of these applications of MALDI-TOF MS are in the preliminary stage of development and require more standardization to provide reliable solutions. The applications of MALDI-TOF MS in the rapid identification of bacteria from positive blood cultures, which allow identification of infection-causing bacteria instantly (Florio et al.) The impact of sample processing methods on the observed variability incorrect identification rates was discussed in this mini-review, but authors missed to give any recommendations to improve the identifications from positive blood culture. Recently, a small modification in the sample processing allowed identification of Brucella infection directly from positive blood culture with MALDI-TOF MS (Bruker) within 2 h, and saved almost 48 h from positive blood culture to correct identification of pathogen (Guo et al., 2019). The development of MALDI-TOF MS based methods for the assessment of antimicrobial resistance in both bacteria and fungi are also in the early stage of development (Florio et al.) More focused studies on the development and validation of new methods will be necessary before MALDI-TOF MS can be used in routine assays for the diagnosis of antimicrobial resistance. Recently, a MALDI-TOF mass spectrometry data acquisition and bioinformatics pipeline (IDBac) is designed by integrating the data from both intact protein and specialized metabolite spectra directly from bacterial cells grown on agar (Clark et al., 2018). This coupling of MALDI-TOF mass spectrometry protein and specialized metabolite analyses resulted in establishing an instant connection between microbial phylogenetic identities with potential environmental functions. Such innovations allow utilization of full capabilities offered by MALDI-TOF MS for the analyses of microbial metabolites and the identification of microorganisms (Clark et al., 2018). MALDI-TOF MS is also finding applications in removing the redundancy, in big microbial discovery and bioprospection projects. MALDI-TOF MS and the bioinformatics pipeline IDBac offers a cost- effective way to rapidly de-replicate the microbial collection based on both the bacterial identity and the natural product producing capacity of colonies in high-throughput (Costa et al., 2019). MALDI-TOF MS based identification becoming a must for the large-scale culturomics experiments, as it is a fast and cost-effective method to filter out multiple conspecific strains or genetically identical clones (Dumolin et al., 2019). Though, the limited database and bias of commercial databases toward microbes of clinical or food safety relevance restrict the application of MALDI-TOF MS. Methods based on similarity measures combined with the clustering of MALDI-TOF mass spectra have been developed to uncouple dereplication from database based identification. Till recently, the identification of identical strains was done by visual interpretation of dendrograms or by using a distance cutoff value (Strejcek et al.). Recently, an algorithm (SPeDE) has been introduced, which enables the rapid analysis and dereplication of isolates using comparison of MALDI-TOF MS profiles (Dumolin et al., 2019). This approach identifies unique spectral features between pairs of spectra and clusters them into operational isolation units (OIUs). MALDI-TOF MS based clustering has also been used to reveal a potential clonal route of transmission of Enterobacter spp. preferentially between general surgery and geriatric wards, which were different from strains of other wards (Florio et al.). This study represents an important source of information about the spreading of Enterobacter, which is an emergent pathogen for its ability to acquire determinants of antimicrobial resistance and role of MALDI-TOF MS in microbiological surveillance in nosocomial setting (Florio et al.). In addition to microorganisms of clinical origin, MALDI-TOF MS offered a high-resolution approach to differentiate environmental isolates of the genus Deinococcus at the subpopulation level, isolated from a freshwater system from other environmental niches (Tuohy et al.). Though the sample size was small (19 isolates) in the study, still it was able to demonstrate the capability of MALDI-TOF MS as a reliable tool to differentiate Deinococcus aquaticus isolates that originate from specific niches (Tuohy et al.). Use of MALDI-TOF MS data for efficient dereplication of recurrent bacterial isolates for downstream analyses was suggested with minimal loss of unique organisms (Strejcek et al.). Challenges in MALDI-TOF MS in Microbial Identification Several studies concluded that low reliable identification of microbes from non-clinical ecosystems such as soil, water, spacecraft assembly cleanrooms, is due to the heavy dominance of MS profiles from clinical isolates in the database (Rahi et al., 2016; Seuylemezian et al.; Strejcek et al.). MALDI-TOF MS based microbial identification platforms allow creating and including a custom, user-specific, and transferable database (Rau et