A Novel Primer Mixture for GH48 Genes: Quantification and Identification of Truly Cellulolytic Bacteria in Biogas Fermenters.
Regina RettenmaierYat Kei LoLarissa SchmidtBernhard MunkIlias LagkouvardosKlaus NeuhausWolfgang SchwarzWolfgang LieblVladimir V ZverlovPublished in: Microorganisms (2020)
Genomic studies revealed the glycoside hydrolases of family 48 (GH48) as a powerful marker for the identification of truly cellulolytic bacteria. Here we report an improved method for detecting cellulolytic bacteria in lab-scale biogas fermenters by using GH48 genes as a molecular marker in DNA and RNA samples. We developed a mixture of primers for the specific amplification of a GH48 gene region in a broad range of bacteria. Additionally, we built a manually curated reference database containing GH48 gene sequences directly linked to the corresponding taxonomic information. Phylogenetic correlation analysis of GH48 to 16S rRNA gene sequences revealed that GH48 gene sequences with 94% identity belong with high confidence to the same genus. Applying this analysis, GH48 amplicon reads revealed that at mesophilic fermenter conditions, 50-99% of the OTUs appear to belong to novel taxa. In contrast, at thermophilic conditions, GH48 gene sequences from the genus Hungateiclostridium dominated with 60-91% relative abundance. The novel primer combinations enabled detection and relative quantification of a wide spectrum of GH48 genes in cellulolytic microbial communities. Deep phylogenetic correlation analysis and a simplified taxonomic identification with the novel database facilitate identification of cellulolytic organisms, including the detection of novel taxa in biogas fermenters.
Keyphrases
- growth hormone
- genome wide
- genome wide identification
- bioinformatics analysis
- copy number
- genome wide analysis
- transcription factor
- dna methylation
- emergency department
- magnetic resonance
- computed tomography
- sewage sludge
- social media
- heavy metals
- quantum dots
- real time pcr
- microbial community
- wastewater treatment
- antibiotic resistance genes
- sensitive detection