Ilgaz Cakin , Barbara Morrissey , Matthew Gordon , Paul P.J. Gaffney , Lucio Marcello , Kenneth Macgregor , Mark A. Taggart
{"title":"Comparing DNA isolation and sequencing strategies for 16S rRNA gene amplicon analysis in biofilm containing environments","authors":"Ilgaz Cakin , Barbara Morrissey , Matthew Gordon , Paul P.J. Gaffney , Lucio Marcello , Kenneth Macgregor , Mark A. Taggart","doi":"10.1016/j.mimet.2024.106921","DOIUrl":null,"url":null,"abstract":"<div><p>Bacteria are primarily responsible for biological water treatment processes in constructed wetland systems. Gravel in constructed wetlands serves as an essential substrate onto which complex bacterial biofilms may successfully grow and evolve. To fully understand the bacterial community in these systems it is crucial to properly isolate biofilms and process DNA from such substrates. This study looked at how best to isolate bacterial biofilms from gravel substrates in terms of bacterial richness. It considered factors including the duration of agitation during extraction, extraction temperature, and enzyme usage. Further, the 16S taxonomy data subsequently produced from Illumina MiSeq reads (using the SILVA 132 ribosomal RNA (rRNA) database on the DADA2 pipeline) were compared with the 16S data produced from Oxford Nanopore Technologies (ONT) MinION reads (using the NCBI 16S database on the EPI2ME pipeline). Finally, performance was tested by comparing the taxonomy data generated from the Illumina MiSeq and ONT MinION reads using the same (SILVA 132) database. We found no significant differences in the effective number of species observed when using different bacterial biofilm detachment techniques. However, enzyme treatment enhanced the total concentration of DNA. In terms of wetland community profiles, relative abundance differences within each sample type were clearer at the genus level. For genus-level taxonomic classification, MinION sequencing with the EPI2ME pipeline (NCBI database) produced bacterial abundance information that was poorly correlated with that from the Illumina MiSeq and DADA2 pipelines (SILVA132 database). When using the same database for each sequencing technology (SILVA132), the correlation between relative abundances at genus-level improved from negligible to moderate. This study provides detailed information of value to researchers working on constructed wetlands regarding efficient biofilm detachment techniques for DNA isolation and 16 s metabarcoding platforms for sequencing and data analysis.</p></div>","PeriodicalId":16409,"journal":{"name":"Journal of microbiological methods","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2024-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of microbiological methods","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167701224000332","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Bacteria are primarily responsible for biological water treatment processes in constructed wetland systems. Gravel in constructed wetlands serves as an essential substrate onto which complex bacterial biofilms may successfully grow and evolve. To fully understand the bacterial community in these systems it is crucial to properly isolate biofilms and process DNA from such substrates. This study looked at how best to isolate bacterial biofilms from gravel substrates in terms of bacterial richness. It considered factors including the duration of agitation during extraction, extraction temperature, and enzyme usage. Further, the 16S taxonomy data subsequently produced from Illumina MiSeq reads (using the SILVA 132 ribosomal RNA (rRNA) database on the DADA2 pipeline) were compared with the 16S data produced from Oxford Nanopore Technologies (ONT) MinION reads (using the NCBI 16S database on the EPI2ME pipeline). Finally, performance was tested by comparing the taxonomy data generated from the Illumina MiSeq and ONT MinION reads using the same (SILVA 132) database. We found no significant differences in the effective number of species observed when using different bacterial biofilm detachment techniques. However, enzyme treatment enhanced the total concentration of DNA. In terms of wetland community profiles, relative abundance differences within each sample type were clearer at the genus level. For genus-level taxonomic classification, MinION sequencing with the EPI2ME pipeline (NCBI database) produced bacterial abundance information that was poorly correlated with that from the Illumina MiSeq and DADA2 pipelines (SILVA132 database). When using the same database for each sequencing technology (SILVA132), the correlation between relative abundances at genus-level improved from negligible to moderate. This study provides detailed information of value to researchers working on constructed wetlands regarding efficient biofilm detachment techniques for DNA isolation and 16 s metabarcoding platforms for sequencing and data analysis.
期刊介绍:
The Journal of Microbiological Methods publishes scholarly and original articles, notes and review articles. These articles must include novel and/or state-of-the-art methods, or significant improvements to existing methods. Novel and innovative applications of current methods that are validated and useful will also be published. JMM strives for scholarship, innovation and excellence. This demands scientific rigour, the best available methods and technologies, correctly replicated experiments/tests, the inclusion of proper controls, calibrations, and the correct statistical analysis. The presentation of the data must support the interpretation of the method/approach.
All aspects of microbiology are covered, except virology. These include agricultural microbiology, applied and environmental microbiology, bioassays, bioinformatics, biotechnology, biochemical microbiology, clinical microbiology, diagnostics, food monitoring and quality control microbiology, microbial genetics and genomics, geomicrobiology, microbiome methods regardless of habitat, high through-put sequencing methods and analysis, microbial pathogenesis and host responses, metabolomics, metagenomics, metaproteomics, microbial ecology and diversity, microbial physiology, microbial ultra-structure, microscopic and imaging methods, molecular microbiology, mycology, novel mathematical microbiology and modelling, parasitology, plant-microbe interactions, protein markers/profiles, proteomics, pyrosequencing, public health microbiology, radioisotopes applied to microbiology, robotics applied to microbiological methods,rumen microbiology, microbiological methods for space missions and extreme environments, sampling methods and samplers, soil and sediment microbiology, transcriptomics, veterinary microbiology, sero-diagnostics and typing/identification.