Characterization of Uncultured Genome Fragment from Soil Metagenomic Library Exposed Rare Mismatch of Internal Tetranucleotide Frequency

Abstract

Exploring the genomic information of a specific uncultured soil bacterium is vital to understand its function in the ecosystem but is still a challenge due to the lack of culture techniques. To examine the genomes of uncultured bacteria, a metagenomic bacterial artificial chromosome library derived from a soil sample was screened for 16S rDNA-containing clones. Five clones (4C6, 5E7, 5G4, 5G12, and 5H7) containing uncultured soil bacteria genome fragment (with low 16S rDNA similarity to isolated bacteria) were selected for sequencing. Clone 5E7 and 5G4 showed only 82 and 83% of 16S rDNA identity to known sequences. Phylogenetic analysis of 16S rDNA indicated that 5E7 and 5G4 were potentially from new class of Chloroflexi. Only one-third of the 5G4 open reading frames have significant hits against HMMER. Internal tetranucleotide frequency analysis indicated that the unknown region of 5G4 was poorly correlated with other parts of the clone, indicating that this section might be obtained through lateral transfer. It was suggested that this region rich for unknown genes is under fast evolution.

Elevational is the main factor controlling the soil microbial community structure in alpine tundra of the Changbai Mountain

“…Taxonomic richness does not follow the classic decreasing or unimodal elevation diversity patterns, which agrees with most studies finding non-significant elevation patterns 52 , 55 , 56 . Shen et al observed that taxonomic richness linearly decreased with increased elevation and phylogenetic diversity exhibited a unimodal pattern with elevation 57 .…”

“…The higher C, N, and P levels with increasing altitudes may contribute to enhanced microbial growth 63 . As previously observed, the bacterial diversity/structure and function was strongly influenced by soil properties 34 , 52 , 64 , 65 . In our research, correlation analyses demonstrated that C- and N-cycling gene (except ammonia-oxidizing archaea) abundance is associated with pH, some of them also correlated with soil moisture, TOC, C/N, and acid phosphatase.…”

“…Contrary to fungal biomass, C- and N-cycling gene abundances did not vary along elevation gradients, but there were significant differences in different vegetation types. Shen et al suggest that soil microbial functional gene richness dramatically increases at the treeline ecotone from temperate forest to alpine tundra in the Changbai Mountains 52 . Different vegetation types with different litter input which can lead to difference in the composition of soil organic matter 53 .…”

Discovery of Novel Biosynthetic Gene Cluster Diversity From a Soil Metagenomic Library

“…Despite these developments in uncovering BGC diversity, direct sequencing does not lend itself to heterologous expression of BGCs in order to identify the encoded secondary metabolites. In order to access and express complete BGCs, bacterial artificial chromosome (BAC) vectors can be used to clone contiguous genomic fragments that can exceed 300 Kb, thereby increasing the probability of obtaining intact BGCs from metagenomic sourced DNA, while also enabling inducible copy number in E. coli and conjugal transfer to heterologous expression hosts ( Wild et al, 2002 ; Aakvik et al, 2009 ; Liu et al, 2010 ; Kakirde et al, 2011 ; Liu et al, 2016 ; Nasrin et al, 2018 ). Functional screening of metagenomic clones typically results in very low hit rates for enzymatic activities ( Healy et al, 1995 ; Thies et al, 2016 ; Lewin et al, 2017 ) and even lower rates for discovering bioactive metabolites ( Tulp and Bohlin, 2005 ); thus, it is desirable to first identify clones containing the target gene or BGC of interest.…”

Table_4.DOCX

“…Despite these developments in uncovering BGC diversity, direct sequencing does not lend itself to heterologous expression of BGCs in order to identify the encoded secondary metabolites. In order to access and express complete BGCs, bacterial artificial chromosome (BAC) vectors can be used to clone contiguous genomic fragments that can exceed 300 Kb, thereby increasing the probability of obtaining intact BGCs from metagenomic sourced DNA, while also enabling inducible copy number in E. coli and conjugal transfer to heterologous expression hosts (Wild et al, 2002;Aakvik et al, 2009;Liu et al, 2010;Kakirde et al, 2011;Liu et al, 2016;Nasrin et al, 2018). Functional screening of metagenomic clones typically results in very low hit rates for enzymatic activities (Healy et al, 1995;Thies et al, 2016;Lewin et al, 2017) and even lower rates for discovering bioactive metabolites (Tulp and Bohlin, 2005); thus, it is desirable to first identify clones containing the target gene or BGC of interest.…”