## 1 Introduction  
Microbes are known as engines of an ecosystem as their growth and metabolisms drive various biogeochemical cycles and mediate many ecological processes such as decomposing organic compounds, solubilizing mineral substances and promoting plant performance [1]. Moreover, microbes also play important roles in removing toxic pollutants and chemical contaminants. For instance, microorganisms transform aromatic compounds into harmless metabolites or less/nontoxic forms [2]. Other harmful metabolites that are converted by microorganisms include hydrocarbon compounds [3], heavy metals [4] and other chemicals with excessive concentrations in an environment [5; 6; 7]. Various tools have been developed for the prediction of ecological functions of microbial taxa derived from amplicon-based next-generation sequencing data. These tools allow us to investigate both community and functional composition of microbes. The usefulness of these tools depends on thorough and global data on microbial community and functions, which would provide deeper insight for microbial ecological research and could be a low-cost alternative to metagenomic sequencing [8; 9]. As a result, many functional prediction tools were generated for both prokaryotic and eukaryotic microorganisms. For example, FUNGuild is a typical functional prediction tool for fungi, providing guild characteristics of the detected taxa, such as saprotroph, pathogen, decomposer or lichenvorous fungi, based on their taxonomic identity [10]. Other tools such as phylogenetic investigation of communities by reconstruction of unobserved states (PICRUST) [11; 12], pathway prediction by phylogenetic placement (PAPRICA) [13], predicting functional profiles from metagenomic 16S rRNA data (Tax4 Fun) [8] and functional annotation of prokaryotic taxa (FAPROTAX) [9] were developed to predict bacterial and archaeal functions. The former three predict the functions based on gene content of detected taxa, whereas the latter is the only tool that uses experimental data on culturable taxa to identify functional groups, metabolic phenotypes or ecologically relevant functions [9]. Furthermore, FAPROTAX may be more preferable for functional prediction of the biogeochemical cycle of environmental samples [9; 14; 15]. The FAPROTAX is a database that maps bacterial or archaeal taxa to metabolic or ecologically relevant functions (i.e., nitrogen fixation, sulfate respiration or hydrocarbon degradation) using literature on culture representatives. This means that if all cultured members of a taxon can perform a function, the function will be assigned to all members of this taxon (cultured and uncultured). The FAPROTAX provides a python script to convert OTUs tables into functional tables based on taxa identified in a sample and functional phenotype of each taxon in the FAPROTAX database. This database was initially built for a study on marine environments, containing over 80 functions and 4600 taxonomic details of bacteria and archaea from oceans [9]. However, FAPROTAX used standard references (in [PERSON]'s manual of systematic bacteriology [16; 17; 18; 19; 20]. The prokaryotes [21] and International Journal of Systematic and Evolutionary Microbiology [22]) for general bacteria and archaea living in both aquatic and terrestrial ecosystems. This implies that the functional assignments are not completely dependent on habitats (aquatic vs. terrestrial systems) and highly dependent on taxonomic information at genus, species or strain levels of a particular bacterial and archaeal taxon. Consequently, many studies have used FAPROTAX for functional annotation of bacteria and archaea on various ecosystems including aquatic [9; 23; 24; 25; 26; 27] and terrestrial systems [28; 29; 30; 31], as well as human and animal microbiome [14; 32]. Despite the compatibility to the soil system, FAPROTAX is still not widely utilized for functional annotation of soil bacteria and archaea because there has been no effort to test the capability of FAPROTAX in soil.