the global human microbiome were reconstructed in 2019 from 9,428 metagenomes. methods for assessing microbial functioning methods for assessing microbial functioning complex microbiome studies cover various areas, starting from the level of complete microbial cells (microscopy, culturomics), followed by the dna (single cell genomics, metabarcoding, metagenomics), rna (metatranscriptomics), protein (metaproteomics), and metabolites (metabolomics). in that order, the focus of the studies shifts from the microbial potential (learning about available microbiota in the given habitat) over the metabolic potential (deciphering available genetic material) towards microbial functioning (e.g., the discovery of the active metabolic pathways). computational modeling of microbiomes has been used to complement experimental methods for investigating microbial function by utilizing multi-omic data to predict complex inter-species and host-species dynamics. a popular in silico method is to combine metabolic network models of microbial taxa present in a community and use a mathematical modeling strategy such as flux balance analysis to predict the metabolic function of the microbial community at a taxon and community-level. as of 2020, understanding remains limited due to missing links between the massive availability of microbiome dna sequence data on the one hand and limited availability of microbial isolates needed to confirm metagenomic predictions of gene function on the other hand. metagenome data provides a playground for new predictions, yet much more data is needed to strengthen the links between sequence and rigorous functional predictions. this becomes obvious when considering that the replacement of one single amino acid residue by another may lead to a radical functional change, resulting in an incorrect functional assignment to a given gene sequence. additionally, cultivation of new strains is needed to help identify the large fraction of unknown sequences obtained from metagenomics analyses, which for poorly studied ecosystems can be more than 70%. depending on the applied method, even in well-studied microbiomes, 40–70% of the annotated genes in fully sequenced microbial genomes have no known or predicted function. as of 2019, 85 of the then established 118 phyla had not had a single species described, presenting a challenge to understanding prokaryotic functional diversity . the number of prokaryotic phyla may reach hundreds, and archaeal ones are among the least studied. the growing gap between the diversity of bacteria and archaea held in pure culture and those detected by molecular methods has led to the proposal to establish a formal nomenclature for not-yet cultured taxa, primarily based on sequence information. according to this proposal, the concept of candidatus species would be extended to the groups of closely related genome sequences, and their names would be published following established rules of bacterial nomenclature. each microbiome system is suited to address different types of questions based on the culturability of microbes, genetic tractability of microbes and host (where relevant), ability to maintain system in laboratory setting, and ability to make host/environment germfree. underlying complexity tradeoffs between experimental questions and complexity of microbiome systems (a) pairwise interactions between the soil bacteria bacillus subtilis and streptomyces spp. are well-suited for characterizing the functions of secondary metabolites in microbial interactions.(b) the symbiosis between bobtail squid and the marine bacterium aliivibrio fischeri is fundamental to understanding host and microbial factors that influence colonization.(c) the use of gnotobiotic mice is crucial for making links between host diet and the effects on specific microbial taxa in a community.