In the current studies we relies to a significant extent on the filterability of the smallest microbial cells often referred as ultra-microcells. Filterability of microorganisms from natural mineral water in C.R.jones et al. (23) research studies confirmed presence of smaller bacterial cells known as ultra-microcells.
These ultra-small bacteria are ambiguous and don’t yet fully understand what they do, Said Prof Banfield, who is the one author of a paper referred as diverse uncultivated ultra-small bacterial cells in groundwater(1). Banfield, et al. passaged metagenomic analysis of the particles collected from groundwater samples through a 0.2-µm filter membrane and 0.1-µm filter membrane (1). The Comparison between these two community shows that the composition of the community 0.1-µm filter membrane was markedly different to that community composition collected on the 0.2-µm filter, there are huge difference between these two filter size (supplementary figure11 A and B). They proved that these cells are small and thus might be enriched by filtration for coupled genomic and ultrastructural characterization. The majority of the bacteria on the 0.1-µm filter were members of the candidate phyla and the majority of the bacteria on the 0.2-µm filter were members of the proteobacteria. Genomic data indicated that Archaea comprise only a small fraction of the community, this will confirm high abundance of terepen in our result because recent study, confirmed terpens have been detected in bacteria and there is no evidence found in archaea (24, 25)
Filtration result from Wang et al. studies confirmed shape and flexibility of a bacterium change its passage through small pore sizes (26). Conclusion about the filtration, range and shape of microorgannisms in which secondary metabolism are occurs are not possible yet because of the inevitable bias in the search for products.
Surface water microbiomes are unique communities and their metagenomes have not been extensively mined for new biosynthesis pathways
The result from many research study give us a clue to study presence of secondary metabolite gene clusters in ultra-small bacterial cell with computational method and metagenomics approach. To best of our knowledge to date only very few studies were performed using computational and metagenomics approaches to investigation for secondary metabolite gene cluster and screened of PKS and NRPS domains. However all of these studies work in composition of the secondary metabolite passage through a 0.2-µm filter membrane and none of them work on the composition of secondary metabolite passage through a 0.1-µm filter membrane. One of these study was conducted by Ludington et al.(7) that they used sample of groundwater from three wells at different depth, use filtration through a 0.22 ?m, DNA extraction, Whole metagenome shotgun sequencing and their result proved that elevated nitrate and rich secondary metabolite biosynthetic capacity in groundwater sample and most secondary metabolites classes belong to fatty acids, saccharides, bacteriocins, non-ribosomal peptide synthases and terpenes, moreover they did not screen biosynthesis gene cluster and PKS and NRPS domains domain. Another secondary metabolite, metagenomic analysis study was conducted by Cuadrat et al. (20) that they collect two surface water samples and use 0.22 ?m filtration membrane and revealed 38 ,46 type I KS domain and 14 ,36 C domain for each samples . From these results they concluded potential of metagenome for rich secondary metabolites. In our result we confirmed 55 type I KS domain and 34 C domain in one sample. Our result show higher KS domain abundance and almost similar C domain. In the study of Foerstner et al. 27, from the environment of Minnesota farm soil 52 type I KS were found. We can conclude our metagenome indicate considerable potential for screen secondary metabolites.
Biosynthetic gene clusters distributed throughout bacteria (28, 29) and almost 7% of bacteria dedicate 7.5% or more of their genomes to secondary metabolism (30, 31). In the current study 190 secondary metabolite gene clusters were found and they are classified according to homologues gene cluster predicted. Among these 190 BGCs, one of this gene show interesting domain and structure (Figure 10) and does not appear homologues to any known biosynthetic clusters. This interesting putative gene cluster was classified in the Transatpks and encoded hypothetical protein from Limnothrix sp. This cluster could be engineered to produce novel gene cluster for future work. Plenty secondary metabolites have been isolated from organisms with unsequenced genomes such as albocycline from bacterium Streptomyces sp (32). This gene cluster contains 13 KS sequences, we checked phylogenetic tree of this KS sequence after trimmed by NAPDOS (figure11) PKSs with known close relationships were cluster together, and result shows trans-AT clade is entirely contained within a Hybrid clade, concluding that the evolution of trans-AT PKSs may have been involved a hybrid ancestor. The shared ancestry reported between type II PKS and FAS sequences, the vast majority of the reference sequences fall into the type I PKS clade.
Figure 10: c00001_NODE_74 Gene Cluster