DNA extraction for 16S rRNA gene analysis to determine genetic diversity in deep sediment communities

AbstractHigh-throughput phylogenetic 16S rRNA gene analysis has permitted to thoroughly delve into microbial community complexity and to understand host-microbiota interactions in health and disease. The analysis comprises sample collection and storage, genomic DNA extraction, 16S rRNA gene amplification, high-throughput amplicon sequencing and bioinformatic analysis. Low biomass microbiota samples (e.g. biopsies, tissue swabs and lavages) are receiving increasing attention, but optimal standardization for analysis of low biomass samples has yet to be developed. Here we tested the lower bacterial concentration required to perform 16S rRNA gene analysis using three different DNA extraction protocols, three different mechanical lysing series and two different PCR protocols. A mock microbiota community standard and low biomass samples (108, 107, 106, 105 and 104 microbes) from two healthy donor stools were employed to assess optimal sample processing for 16S rRNA gene analysis using paired-end Illumina MiSeq technology. Three DNA extraction protocols tested in our study performed similar with regards to representing microbiota composition, but extraction yield was better for silica columns compared to bead absorption and chemical precipitation. Furthermore, increasing mechanical lysing time and repetition did ameliorate the representation of bacterial composition. The most influential factor enabling appropriate representation of microbiota composition remains sample biomass. Indeed, bacterial densities below 106 cells resulted in loss of sample identity based on cluster analysis for all tested protocols. Finally, we excluded DNA extraction bias using a genomic DNA standard, which revealed that a semi-nested PCR protocol represented microbiota composition better than classical PCR. Based on our results, starting material concentration is an important limiting factor, highlighting the need to adapt protocols for dealing with low biomass samples. Our study suggests that the use of prolonged mechanical lysing, silica membrane DNA isolation and a semi-nested PCR protocol improve the analysis of low biomass samples. Using the improved protocol we report a lower limit of 106 bacteria per sample for robust and reproducible microbiota analysis.

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Human Isolates of Large Colony-Forming β Hemolytic Group G Streptococci form a Distinct Clade upon 16S rRNA Gene Analysis

Streptococci and the Host - Advances in Experimental Medicine and Biology ◽

10.1007/978-1-4899-1825-3_87 ◽

1997 ◽

pp. 363-365 ◽

Cited By ~ 3

Author(s):

Norbert Schnitzler ◽

Gerhard Haase ◽

Andreas Podbielski ◽

Achim Kaufhold ◽

Christoph Lämmler ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Gene Analysis ◽

Rrna Gene ◽

16S Rrna Gene Analysis ◽

Group G Streptococci ◽

Large Colony

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Resource Development and Investigation of Novel Species from Unidentified Pathogens in NCCP using MALDI-TOF MS and 16S rRNA Gene Analysis

Journal of Bacteriology and Virology ◽

10.4167/jbv.2016.46.4.201 ◽

2016 ◽

Vol 46 (4) ◽

pp. 201

Author(s):

Won Seon Yu ◽

Kyeong Min Lee ◽

Kyu Jam Hwang

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Novel Species ◽

Resource Development ◽

Gene Analysis ◽

Rrna Gene ◽

16S Rrna Gene Analysis ◽

Maldi Tof Ms ◽

Maldi Tof ◽

Tof Ms

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Clinical Relevance of the Microbiome in Odontogenic Abscesses

Biology ◽

10.3390/biology10090916 ◽

2021 ◽

Vol 10 (9) ◽

pp. 916

Author(s):

Sebastian Böttger ◽

Silke Zechel-Gran ◽

Daniel Schmermund ◽

Philipp Streckbein ◽

Jan-Falco Wilbrand ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Oral Microbiome ◽

Molecular Methods ◽

Gene Analysis ◽

Rrna Gene ◽

16S Rrna Gene Analysis ◽

Cultural Methods ◽

Odontogenic Abscess ◽

Polymicrobial Infections

Odontogenic abscesses are usually caused by bacteria of the oral microbiome. However, the diagnostic culture of these bacteria is often prone to errors and sometimes fails completely due to the fastidiousness of the relevant bacterial species. The question arises whether additional pathogen diagnostics using molecular methods provide additional benefits for diagnostics and therapy. Experimental 16S rRNA gene analysis with next-generation sequencing (NGS) and bioinformatics was used to identify the microbiome of the pus in patients with severe odontogenic infections and was compared to the result of standard diagnostic culture. The pus microbiome was determined in 48 hospitalized patients with a severe odontogenic abscess in addition to standard cultural pathogen detection. Cultural detection was possible in 41 (85.42%) of 48 patients, while a pus-microbiome could be determined in all cases. The microbiomes showed polymicrobial infections in 46 (95.83%) cases, while the picture of a mono-infection occurred only twice (4.17%). In most cases, a predominantly anaerobic spectrum with an abundance of bacteria was found in the pus-microbiome, while culture detected mainly Streptococcus, Staphylococcus, and Prevotella spp. The determination of the microbiome of odontogenic abscesses clearly shows a higher number of bacteria and a significantly higher proportion of anaerobes than classical cultural methods. The 16S rRNA gene analysis detects considerably more bacteria than conventional cultural methods, even in culture-negative samples. Molecular methods should be implemented as standards in medical microbiology diagnostics, particularly for the detection of polymicrobial infections with a predominance of anaerobic bacteria.

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