High-throughput 16S rRNA gene amplicon sequencing technology is widely applied for environmental microbiota structure analysis to derive knowledge that informs microbiome-based surveillance and oriented bioengineering. However, it remains elusive how the selection of 16S rRNA gene hypervariable regions and reference databases affects microbiota diversity and structure profiling. This study systematically evaluated the fitness of different frequently used reference databases (i.e. SILVA 138 SSU, GTDB bact120_r207, Greengenes 13_5 and MiDAS 4.8) and primers of 16S rRNA gene in microbiota profiling of anaerobic digestion and activated sludge collected from a full-scale swine wastewater treatment plant (WWTP). The comparative results showed that MiDAS 4.8 achieved the highest levels of taxonomic diversity and species-level assignment rate. For whichever sample groups, microbiota richness captured by different primers decreased in the following order: V4 > V4-V5 > V3-V4 > V6-V8/V1-V3. Using primer-bias-free metagenomic data results as the judging standard, V4 region also best characterized microbiota structure and well represented typical functional guilds (e.g. methanogens, ammonium oxidizers and denitrifiers), while V6-V8 regions largely overestimated the archaeal methanogens (mainly Methanosarcina ) by over 30 times. Therefore, MiDAS 4.8 database and V4 region are recommended for best simultaneous analysis of bacterial and archaeal community diversity and structure of the examined swine WWTP.
Keyphrases
- wastewater treatment
- antibiotic resistance genes
- single cell
- copy number
- genome wide
- high throughput
- anaerobic digestion
- healthcare
- big data
- genome wide identification
- microbial community
- physical activity
- dna methylation
- gene expression
- emergency department
- risk assessment
- ionic liquid
- artificial intelligence
- sewage sludge
- heavy metals